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We propose two new authentication schemes for the cloud that support private attribute-based authentication services. The basic scheme is non-anonymous attribute-based authentication scheme. The extended scheme of the basic scheme is fully anonymous attribute-based authentication scheme to realize full anonymity and unlinkability services. In the proposed schemes, a user is authenticated by the remote server if the intersection of the set of his/her assigned attributes and the server’s required attributes exceeds a satisfactory predefined level. Unlike existing attribute-based encryption and signature schemes that require the user to perform significant amount of elliptic curve bilinear pairings and modular exponentiations, and require the user to hold a significantly long decryption/signature key, in our schemes the user is not required to perform any bilinear pairings. With a fixed length private key, independent of the number of attributes, the cloud user performs only few exponentiations by which he/she is able to authenticate himself/herself to the remote server and establish a session key with the server with the condition that he/she satisfies a predefined level of the server’s attributes requirement. Therefore, our schemes are suitable for implementation on devices with limited resources. We provide the rigorous security of the proposed schemes and complexity analysis of our schemes. Finally, the security and performance comparisons of our schemes with the existing related schemes show that our schemes outperform other existing schemes. [ABSTRACT FROM AUTHOR]

As is well known, the additional low-order harmonic currents and the huge computation amount of the cost function value with all available control sets are the two special issues of finite-control-set model predictive current control (FCS-MPCC) for multiphase inverters. Thus, this paper proposes a FCS-MPCC scheme with duty-ratio optimization for five-phase inverters. First, a group of the reconstructed virtual voltage vectors (V3) with low-order harmonic elimination is defined and employed as the control sets in FCS-MPCC scheme. Thus, it leads to no requirement for harmonic items and weighting factors existing in the cost function. Then, a combination of zero vectors and the selected V3 during each control horizon is adopted to rearrange the pulse sequence, which can realize constant switching frequency. In addition, the durations of the selected V3 and zero vectors during each control horizon are also estimated to minimize the steady-state current ripples in different subspaces based on the cost function optimization. Finally, a comparison of the proposed V3-FCS-MPCC scheme and the other FCS-MPCCs are presented in simulation and experimental test. Simulation and experimental results verify that the proposed V3-FCS-MPCC scheme can remain the simplified structure, fast dynamic performance, constant switching frequency, and achieve minimum current ripples in different subspaces. [ABSTRACT FROM PUBLISHER]

The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. Reliability is one of the most important challenges for the MMC consisting of a large number of power electronic devices. The diode open-circuit fault in the submodule (SM) is an important issue for the MMC, which would affect the performance of the MMC and disrupt the operation of the MMC. This paper analyzes the impact of diode open-circuit failures in the SMs on the performance of the MMC and proposes a protection scheme for the MMC under diode open-circuit faults. The proposed protection scheme not only can effectively eliminate the possible caused high voltage due to the diode open-circuit fault but also can quickly detect the faulty SMs, which effectively avoids the destruction and protects the MMC. The proposed protection scheme is verified with a downscale MMC prototype in the laboratory. The results confirm the effectiveness of the proposed protection scheme for the MMC under diode open-circuit faults. [ABSTRACT FROM PUBLISHER]

Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure. [ABSTRACT FROM AUTHOR]

Public key encryption with keyword search (PEKS) is a cryptographic primitive that allows a secure search for desired keywords of data users by a cloud server using a search token. To the best of our knowledge, we propose the first practical, semantic secure, and post-quantum PEKS scheme based on rank metric codes. The proposed scheme is secure against keyword guessing attack, reaction attack, and key exposure, and enjoys conjunctive keyword search, verifiability of search results using Bloom filter and garbled Bloom filter. We implement the scheme with C++ programming language on a desktop computer. At the security level of 256 bits, the scheme performs all the necessary steps for encryption, keyword search, and verification of search results for one keyword in 22.5 milliseconds. Furthermore, the public key length at this security level is about 5 kilobytes. We show that the scheme is more efficient than the existing relevant post-quantum ones. [Display omitted] • A public key with keyword search scheme based on rank metric codes is proposed. • The scheme is secure under chosen keyword, keyword guessing, and reaction attacks. • The scheme is secure against quantum processors, having a small public key. • The scheme supports the verifiability of search results and conjunctive keyword search. [ABSTRACT FROM AUTHOR]

The Self-Organizing Networks (SON) paradigm proposes a set of functions to automate network management in mobile communication networks. Within SON, the purpose of Self-Healing is to detect cells with service degradation, diagnose the fault cause that affects them, rapidly compensate the problem with the support of neighboring cells and repair the network by performing some recovery actions. The diagnosis phase can be designed as a classifier. In this context, hybrid ensembles of classifiers enhance the diagnosis performance of expert systems of different kinds by combining their outputs. In this paper, a novel scheme of hybrid ensemble of classifiers is proposed as a two-step procedure: a modeling stage of the baseline classifiers and an application stage, when the combination of partial diagnoses is actually performed. The use of statistical models of the baseline classifiers allows an immediate ensemble diagnosis without running and querying them individually, thus resulting in a very low computational cost in the execution stage. Results show that the performance of the proposed method compared to its standalone components is significantly better in terms of diagnosis error rate, using both simulated data and cases from a live LTE network. Furthermore, this method relies on concepts which are not linked to a particular mobile communication technology, allowing it to be applied either on well established cellular networks, like UMTS, or on recent and forthcoming technologies, like LTE-A and 5G. [ABSTRACT FROM AUTHOR]

In this paper, we show that large annotated data sets have great potential to provide strong priors for saliency estimation rather than merely serving for benchmark evaluations. To this end, we present a novel image saliency detection method called saliency transfer. Given an input image, we first retrieve a support set of best matches from the large database of saliency annotated images. Then, we assign the transitional saliency scores by warping the support set annotations onto the input image according to computed dense correspondences. To incorporate context, we employ two complementary correspondence strategies: a global matching scheme based on scene-level analysis and a local matching scheme based on patch-level inference. We then introduce two refinement measures to further refine the saliency maps and apply the random-walk-with-restart by exploring the global saliency structure to estimate the affinity between foreground and background assignments. Extensive experimental results on four publicly available benchmark data sets demonstrate that the proposed saliency algorithm consistently outperforms the current state-of-the-art methods. [ABSTRACT FROM PUBLISHER]

Masquerade attackers are internal intruders acting through impersonating legitimate users of the victim system. Most of the proposals for their detection suggested recognition methods based on the comparison of use models of the protected environment. However recent studies have shown their vulnerability against adversarial attacks based on imitating the behavior of legitimate users. In order to contribute to their identification, this article introduces a novel detection method robust against evasion strategies based on mimicry. The proposal described two levels of information processing: analysis and verification. At the analysis stage, local alignment algorithms are implemented. In this way it is possible to score the similarity between action sequences performed by users, bearing in mind their regions of greatest resemblance. On the other hand, a novel validation scheme based on the statistical non-parametric U-test is implemented. Through this it is possible to refine the labeling of sequences to avoid making hasty decisions when their nature is not sufficiently clear. In order to strengthen their effectiveness against mimicry attacks, the analysis of the monitored sequences is performed in concurrency. This involves partitioning long sequences with two purposes: making subsequences of small intrusions more visible and analyzing new sequences when suspicious situations occur, such as the execution of never before seen commands or the discovery of potentially harmful activities. The proposal has been evaluated from the functional standard SEA and mimicry attacks. Promising experimental results have been shown, demonstrating great precision against conventional masqueraders (TPR=98.3%, FPR=0.77%) and a success rate of 80.2% when identifying mimicry attacks, hence outperforming the best contributions of bibliography. [ABSTRACT FROM AUTHOR]

Predicate encryption is a public-key encryption that supports attribute-hiding as well as payload-hiding and achieves high flexibility in terms of access control. Since Katz, Sahai, and Waters first proposed the predicate encryption scheme in 2008, several predicate encryption schemes have been published. Unfortunately these are impractical as they require O(n) pairing computations for decryption with considerably large sized public parameters, secret key, and ciphertext, where n is the dimension of the attribute/predicate vectors. In this paper, we propose a very efficient predicate encryption scheme that requires only n exponentiation plus three pairing computations for decryption with shorter sized public parameters, secret key, and ciphertext. The proposed scheme is proven selective attribute-secure against chosen-plaintext attacks in the standard model under the Asymmetric Decisional Bilinear Diffie-Hellman assumptions. [ABSTRACT FROM AUTHOR]

The growing demand on the performance of transparent computing systems requires good cache schemes in order to overcome the prolonged network latency. However, evaluating cache schemes, especially measuring the performance of a transparent computing system with particular cache scheme remains challenging. This is because neither method is available to evaluate the effectiveness and efficiency of the cache schemes in transparent computing, nor the simulator has been developed to measure the system performance under particular cache schemes. In this paper, we propose TranSim, a full-featured, high-performance simulation framework for transparent computing. For the first time, TranSim introduces a methodology to evaluate the performance of multi-level cache hierarchies in transparent computing under different cache configurations and cache replacement policies. TranSim can also demonstrate the behavior and performance of the entire transparent computing system rather than only the cache miss/hit rate. Using TranSim, the system designer can quickly evaluate the effectiveness of cache schemes along with the system performance. We construct several experiments to evaluate the effectiveness and efficiency of TranSim. Results show that TranSim can accurately output the performance of both the cache hierarchy and the entire transparent computing system. [ABSTRACT FROM AUTHOR]

Continuous scaling of process technology increases variations in transistors. The process variations cause large fluctuations in the access times of static random-access memory (SRAM) cells. Caches made of those SRAM cells cannot be accessed within the target clock cycle time, which reduces the yield of processors. Many schemes have been proposed to combat these access time failures in caches. However, these schemes are limited in their coverage and do not scale well at high failure rates. We propose a new level one (L1) cache architecture employing multi-cycle cell access (MCCA) and subarray-level parallel access (SLPA). MCCA eliminates all access-time failures in L1 caches. SLPA minimizes the performance impact of cache bandwidth loss due to MCCA. For further performance improvement, architectural techniques are proposed. Our experimental results show that our proposed L1 cache architecture incurs a performance hit of less than 1.2 percent compared to the conventional cache architecture with no access time failure. Our proposed architecture is not sensitive to access time failure rates and has a low overhead compared with previously proposed competitive schemes. [ABSTRACT FROM AUTHOR]

Conventional feedback control systems cannot perform well under strong disturbances. Cascade control is an alternative approach to the classical single-input single output-control systems to improve the performance of the control system, especially in the case of disturbances. The general approach to identify the tuning parameters of the controllers used in the inner and the outer loop of the cascade controller structure is to tune the inner and the outer loop in a strict sequence. Here, simultaneous tuning of the inner and outer loop controllers is given. Tuning parameters of the inner and outer loop controllers are determined using a genetic algorithm. Simulation results for stable, unstable and integrating processes in the cascade control scheme are provided to illustrate the performance of the proposed controller design method. [ABSTRACT FROM AUTHOR]

This paper presents an extension of the central scheme of Kurganov and Tadmor (2000) to work with solvers based on conservative face fluxes, which are usual in the solution of incompressible flows by the Finite Volume Method. The proposed scheme retains the desirable properties of simplicity, low numerical viscosity and multidimensionality, and it works on general non-staggered polyhedral meshes. It is applied within a mixture multiphase solver to discretize the mass conservation equation of one of the phases. A series of cases are solved which show that the proposed extension is significantly more robust and monotonicity-preserving than the straightforward application of the Kurganov–Tadmor scheme. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel fault detection and identification (FDI) scheme for a class of nonlinear systems with model uncertainty. At the heart of this approach is an on-line approximator, referred to as fault tracking approximator (FTA). Differently from the other approximators, the FTA uses iterative algorithms to detect and identify nonlinear system faults, even in the presence of model uncertainty, which is motivated by predictive control theory and iterative learning control theory. The FTA can simultaneously detect and identify the shape and magnitude of the faults. The rigorous stability analysis and fault tracking properties of the FTA are also proved. Finally, two examples are given to illustrate the feasibility and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel space vector modulation (SVM) method combined with a modified four-step commutation to achieve a perfect zero common-mode voltage (CMV) for matrix converters (MCs). The new SVM method was developed by using only rotating input voltage vectors, which results in the CMV for MCs being zero. However, it causes some noise in practical applications that drive MCs with traditional four-step commutation. In order to solve this noise problem, a modified four-step commutation is also proposed to perfectly eliminate the CMV for MCs without any noise. In the modified four-step commutation, a delay time is designed to deal with misjudgment of input voltages. The proposed SVM method and four-step commutation are easily implemented via software and achieve good performance in input/output current waveforms. Prototype experiments were carried out to evaluate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

In high frequency induction heating systems, the effective load parameters change during the different operating conditions. It is necessary to maintain constant input voltage to the induction heating load to improve the quality of the heating. The resonant based high frequency converter is generally used for these applications for the reduction of switching losses. The resonant condition is also affected during the variation in load parameters. The controller should provide a good voltage regulation with less response time and less overshoot during the loading conditions. In this paper, a load adaptive fuzzy logic control scheme is proposed to perform the voltage control of the high frequency inverter under variable load conditions. A frequency tracking control system is also employed for the inverter system using the phase lock loop. The phase lock loop ensures the resonant frequency operation of the inverter during the change in load parameters. The state space model of the system is discussed to study the inverter during different operating conditions. The fuzzy logic controller based closed loop control scheme is developed using the MATLAB simulation tool. The responses of the conventional and fuzzy logic controllers are studied for load voltage regulation and the effectiveness of the control schemes is verified. The dynamic behavior of the system is studied under no load and loaded conditions with the two controllers. The fuzzy based closed loop control scheme improves the dynamic response of the system compared to the conventional controller. The response of the induction heating system is validated with a hardware prototype. The results are presented in order to confirm the proposed control strategy. [ABSTRACT FROM AUTHOR]

A peak-to-average power ratio (PAPR) reduction method for an orthogonal frequency division multiplexing (OFDM) system based on a combination of a partial transmit sequence (PTS) scheme with the backtracking search optimization algorithm (BSA) is proposed. The PTS scheme shows good PAPR reduction performance; however, it requires a complex computation to search the set of optimum phase factors, especially for high-speed data transmissions. To minimize the complexity of the search for optimum phase factors, the PTS scheme is combined with the BSA. The BSA is a new and efficient population-based evolutionary search algorithm for real-valued optimization problems. A set of simulations is conducted for the PAPR reduction performance and computational complexity comparisons of the BSA-PTS scheme with different PTS schemes. Simulation results indicate that the BSA-PTS scheme yields an effective PAPR reduction performance with low computational complexity. [ABSTRACT FROM AUTHOR]

The problem of finding similar strings is very important in most real life applications including spell-checking, data cleaning, next generation sequencing, and alignment. In order to query and manage string data online, scalable algorithms and frameworks are essential. Scalable frameworks and algorithms have been introduced in the past few years. However, these frameworks mainly deal with caching and querying structured data. They do not deal with fuzzy queries, where we need to search for an approximate string. In this paper, we propose an edit distance aware filtering algorithm for all kinds of approximate string search problems. We also propose a novel name spell-check engine mainly for social networks. Our experiments show that our edit distance aware filtering mechanism alone improves the query processing time and throughput by almost 30%. Additionally, our name spell-check engine improved the name spell-check response time and throughput almost 10 times by using our filtering scheme and some domain specific observations. [ABSTRACT FROM AUTHOR]

Extended Producer Responsibility (EPR) schemes are adopted not only to promote collection and recycling of waste products but also to close material loops and incentivise ecodesign. These outcomes are also part of creating a more circular economy. Evaluations of best practices can inform how to further optimise systems towards more ambitious collection, recycling and recovery of both hazardous and critical materials. Gas discharge lamps in particular are a key product category in this regard, considering both the presence of mercury and of rare earth materials in this waste stream. Nordic countries in particular are known for advanced collection and recycling systems and this article compares the EPR systems for gas discharge lamps. The EPR systems for lamps are evaluated using theory-based evaluation approaches to analyse both the performance of lamp EPR systems and challenges perceived by key stakeholders. The cases were constructed based on primary and secondary literature, statistical data, and interviews with stakeholders. The findings indicate that the collection and recycling performance is generally still high for gas discharge lamps in the Nordic countries, despite some differences in approach and structure of the EPR systems, but there remain opportunities for further improvement. In terms of EPR goals, there is evidence of improved waste management of these products as a result of the systems; however, there also remain significant challenges, particularly in terms of ecodesign incentives. The key factors for best practice are discussed, including aspects of the rule base, infrastructure, and operations. The particular characteristics of this waste category, including the rapidly changing technology, also pose challenges for EPR systems in the future. [ABSTRACT FROM AUTHOR]

Autonomous cluster operation such as cluster reconfiguration is one of the enabling technologies for fractionated spacecraft. By virtue of the multi-agent system theory, this paper presents an organizational architecture for fractionated spacecraft, which not only enables autonomous cluster operations but also facilitates its non-traditional attributes. Within this organizational architecture, a decentralized framework is proposed to solve cluster reconfiguration problems based on primal and dual decomposition, where subgradient methods are adopted to include reconfiguration cases with non-differentiable objectives. Two typical constraints are considered: final configuration constraints representing coupling variables and collision avoidance constraints representing coupling constraints, both of which are non-convex. General schemes are proposed to convexify those constraints via the linearization and convex restriction technology. Then final configuration constraints are tackled by primal decomposition, while collision avoidance constraints by dual decomposition. To the end, multi-level primal and dual decompositions are employed to solve reconfiguration problems with both coupling variables and coupling constraints. For illustration an example of in-plane cluster reconfiguration is solved and compared with the centralized approach the solution is optimal. [ABSTRACT FROM AUTHOR]

We compared the precision of simple random sampling (SimRS) and seven types of stratified random sampling (StrRS) schemes in estimating regional mean of water-limited yields for two crops (winter wheat and silage maize) that were simulated by fourteen crop models. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, especially when the sensitivity behavior of a crop model is known. [ABSTRACT FROM AUTHOR]

With the increasing availability of medical IoT devices, it becomes feasible to collect health contexts from personal IoT devices and perform analytics to assess the health conditions and identify potential diseases. However, there exist technical challenges in developing such personal healthcare applications; transforming disease diagnosis methods of physicians in machine-readable forms and software implementation of the medical analytic schemes. In this paper, we present a methodology foundation for analyzing medical contexts. That is, we formalize five representative medical diagnosis schemes for personal healthcare application. [ABSTRACT FROM AUTHOR]

Buildings account for nearly 40 percent of the total energy consumption in the United States. As a critical step toward smart cities, it is essential to intelligently manage and coordinate the building operations to improve the efficiency and reliability of overall energy system. With the advent of smart meters and two-way communication systems, various energy consumptions from smart buildings can now be coordinated across the smart grid together with other energy loads and power plants. In this paper, we propose a comprehensive framework to integrate the operations of smart buildings into the energy scheduling of bulk power system through proactive building demand participation. This new scheme enables buildings to proactively express and communicate their energy consumption preferences to smart grid operators rather than passively receive and react to market signals and instructions such as time varying electricity prices. The proposed scheme is implemented in a simulation environment. The experiment results show that the proactive demand response scheme can achieve up to 10 percent system generation cost reduction and 20 percent building operation cost reduction compared with passive demand response scheme. The results also demonstrate that the system cost savings increase significantly with more flexible load installed and higher percentage of proactive customers participation level in the power network. [ABSTRACT FROM AUTHOR]

Audio represents one of the most appealing yet least exploited modalities in wireless sensor networks, due to the potentially extremely large data volumes and limited wireless capacity. Therefore, how to effectively collect audio sensing information remains a challenging problem. In this paper, we propose a new paradigm of audio information collection based on the concept of audio-on-demand. We consider a sink-free environment targeting for disaster management, where audio chunks are stored inside the network for retrieval. The difficulty is to guarantee a high search success rate without infrastructure support. To solve the problem, we design a novel replication algorithm that deploys an optimal number of O(\sqrtn) replicas across the sensor network. We prove the optimality of the energy consumption of the algorithm. We implement a sink-free audio-on-demand (SAoD) WSN system, and conduct extensive simulations to evaluate the performance and efficiency of our design. The experimental results show that our design can provide satisfactory quality of audio-on-demand service with short startup latency and slight playback jitter. Extensive simulation results show that this design achieves a search success rate of 98 percent while reducing the search energy consumption by an order of magnitude compared with existing schemes. [ABSTRACT FROM AUTHOR]

Even though 3D flash memory presents a grand opportunity to huge-capacity non-volatile memory, it suffers from serious program disturbance problems. In contrast to the past efforts in error correction codes and the work in trading the space utilization for reliability, we propose a disturbance-relaxation scheme that can alleviate the negative effects caused by program disturbance inside a physical block. This scheme does not introduce any extra overheads on encoding or storing of extra redundant data. In particular, a methodology is proposed to reduce the data error rate by distributing unavoidable disturbance errors to the flash-memory space of invalid data, with the considerations of the physical organization of 3D flash memory. A series of experiments was conducted based on real multi-layer 3D flash chips, and it showed that the proposed scheme could significantly enhance the reliability of 3D flash memory. [ABSTRACT FROM AUTHOR]

Dynamic random access memory (DRAM) requires periodic refresh operations to retain its data. In practice, DRAM retention times are normally distributed from 64 ms to several seconds. However, the conventional refresh method uses 64 ms as the refresh interval, since it applies the same refresh interval to all DRAM rows. Thus, the conventional refresh method results in unnecessary refresh operations (eventually, energy waste) to the DRAM rows whose retention times are longer than 64 ms. In this paper, we propose a practical refresh scheme that exploits refresh effect of DRAM read operations to reduce refresh overhead. Our proposed scheme applies a refresh interval longer than the conventional refresh interval (64 ms) to the DRAM chip. In this case, weak DRAM rows (DRAM rows whose retention times are shorter than the refresh interval of the DRAM chip) cannot retain their data. In order to retain the data stored in the weak DRAM rows, the memory controller issues read operations to the weak DRAM rows every required refresh interval for the weak DRAM rows. Our evaluation results show that our proposed scheme with 192 ms refresh interval reduces average refresh energy consumption up to 66.0 percent, which in turn reduces average DRAM energy consumption up to 31.8 percent, compared to the conventional refresh method (64 ms). Our proposed scheme requires no modification to internal DRAM chip structures, but it only adds a small weak row buffer (the buffer for the weak row information) to the memory controller, which has a negligible area overhead. [ABSTRACT FROM AUTHOR]

DDoS attack source traceback is an open and challenging problem. Deterministic packet marking (DPM) is a simple and effective traceback mechanism, but the current DPM based traceback schemes are not practical due to their scalability constraint. We noticed a factor that only a limited number of computers and routers are involved in an attack session. Therefore, we only need to mark these involved nodes for traceback purpose, rather than marking every node of the Internet as the existing schemes doing. Based on this finding, we propose a novel marking on demand (MOD) traceback scheme based on the DPM mechanism. In order to traceback to involved attack source, what we need to do is to mark these involved ingress routers using the traditional DPM strategy. Similar to existing schemes, we require participated routers to install a traffic monitor. When a monitor notices a surge of suspicious network flows, it will request a unique mark from a globally shared MOD server, and mark the suspicious flows with the unique marks. At the same time, the MOD server records the information of the marks and their related requesting IP addresses. Once a DDoS attack is confirmed, the victim can obtain the attack sources by requesting the MOD server with the marks extracted from attack packets. Moreover, we use the marking space in a round-robin style, which essentially addresses the scalability problem of the existing DPM based traceback schemes. We establish a mathematical model for the proposed traceback scheme, and thoroughly analyze the system. Theoretical analysis and extensive real-world data experiments demonstrate that the proposed traceback method is feasible and effective. [ABSTRACT FROM AUTHOR]

To guarantee reliability, bulk data dissemination relies on the negotiation scheme in which senders and receivers negotiate transmission schedule through a three-way handshake procedure. However, we find negotiation incurs a long dissemination time and seriously defers the network-wide convergence. On the other hand, the flooding approach, which is conventionally considered inefficient and energy-consuming, can facilitate bulk data dissemination if appropriately incorporated. This motivates us to pursue a delicate tradeoff between negotiation and flooding in the bulk data dissemination. We propose SurF (Survival of the Fittest), a bulk data dissemination protocol which adaptively adopts negotiation and leverages flooding opportunistically. SurF incorporates a time-reliability model to estimate the time efficiencies (flooding versus negotiation) and dynamically selects the fittest one to facilitate the dissemination process. We implement SurF in TinyOS 2.1.1 and evaluate its performance with 40 TelosB nodes. The results show that SurF, while retaining the dissemination reliability, reduces the dissemination time by 40 percent in average, compared with the state-of-the-art protocols. [ABSTRACT FROM AUTHOR]

The network-based mobility management is adapted to the OpenFlow architecture for mobility service at Software Defined Networking (SDN), and data structure for mobility service is proposed. SDN is a newly proposed Internet architecture which decouples the data and control planes, and mobility management is one of the most important issues in SDN. In order to provide mobility management service by utilizing the mobility scheme proposed earlier in a new network environment, the existing mobility schemes need to be modified. Particularly, the characters of the network environment need to be considered when designing the function of the network entities and data structure. Our proposed mobility management scheme is focused on the centralized control mechanism of SDN. We referred to Proxy Mobile IPv6 (PMIPv6) and OpenFlow-based PMIPv6 with a centralized mobility management controller (OPMIPv6-C). It has a merged data structure for the mobility service on SDN controller and minimizes the number of switches which need flow table modification at handover. At the performance analysis chapter, we compare the signaling cost at the registration and handover phase, packet delivery cost, and handover latency between the proposed scheme and OPMIPv6-C. [ABSTRACT FROM AUTHOR]

Device design in nanoelectronics commonly yields strongly coupled problems in the time domain. The formal solution of these problems implies a monolithic approach that is typically characterized by a large sparse matrix system. In this paper, an error correction method is described in the context of electrothermal coupling modeling of device structures. The method avoids the computational burden of the monolithic solution, while retaining the convergence order in time. This is accomplished by solving an error equation in a recursive fashion. Thereby, the method can also take a low-order scheme and promote it to a high-order one and can be integrated with a sub-problem-wise order reduction technique. [ABSTRACT FROM AUTHOR]

In the context of Identity-Based Encryption (IBE), both revocation and delegation of key generation are important functionalities. Although a number of IBE schemes with either efficient revocation or efficient delegation of key generation functionality have been proposed, an important open problem is efficiently delegating both the key generation and revocation functionalities in IBE systems. Seo and Emura (2014) [25] proposed the first realization of Revocable Hierarchical IBE (RHIBE), a sole IBE scheme that achieves both functionalities simultaneously. However, their approach implements history-preserving updates, wherein a low-level user must know the history of key updates performed by ancestors in the current time period, and it renders the scheme very complex. In this paper, we present a new method to construct RHIBE that implements history-free updates. Our history-free approach renders the scheme simple and efficient. As a second contribution, we redefine the security model for RHIBE to ensure security against insiders , where adversaries are allowed to obtain all internal system information, e.g., state information. In addition, we also consider the decryption key exposure attack, which was considered by Seo and Emura (2013) [23] . Further, we propose two RHIBE schemes with shorter secret keys and constant size ciphertexts that implement the aforementioned history-free updates approach and security model. For revocation, our constructions use the Complete Subtree (CS) method and the Subset Difference (SD) method. Both schemes are selectively secure in the standard model under the q -weak Bilinear Diffie–Hellman Inversion assumption. [ABSTRACT FROM AUTHOR]

Privacy protection is the primary concern when RFID applications are deployed in our daily lives. Due to the computational power constraints of passive tags, non-encryption-based singulation protocols have been recently developed, in which wireless jamming is used. However, the existing private tag access protocols without shared secrets rely on impractical physical layer assumptions, and thus they are difficult to deploy. To tackle this issue, we first redesign the architecture of RFID system by dividing an RF reader into two different devices, an RF activator and a trusted shield device (TSD). Then, we propose a novel coding scheme, namely Random Flipping Random Jamming (RFRJ), to protect tags’ content. Unlike the past work, the proposed singulation protocol utilizes only the physical layer techniques that are already implemented. Analyses and simulation results validate our distributed architecture with the RFRJ coding scheme, which defends tags’ privacy against various adversaries including the random guessing attack, correlation attack, ghost-and-leech attack, and eavesdropping. [ABSTRACT FROM AUTHOR]

Broadcast encryption (BE) schemes allow a sender to securely broadcast to any subset of members but require a trusted party to distribute decryption keys. Group key agreement (GKA) protocols enable a group of members to negotiate a common encryption key via open networks so that only the group members can decrypt the ciphertexts encrypted under the shared encryption key, but a sender cannot exclude any particular member from decrypting the ciphertexts. In this paper, we bridge these two notions with a hybrid primitive referred to as contributory broadcast encryption (ConBE). In this new primitive, a group of members negotiate a common public encryption key while each member holds a decryption key. A sender seeing the public group encryption key can limit the decryption to a subset of members of his choice. Following this model, we propose a ConBE scheme with short ciphertexts. The scheme is proven to be fully collusion-resistant under the decision $n$ -Bilinear Diffie-Hellman Exponentiation (BDHE) assumption in the standard model. Of independent interest, we present a new BE scheme that is aggregatable. The aggregatability property is shown to be useful to construct advanced protocols. [ABSTRACT FROM AUTHOR]

Three-body effects play an important role for obtaining quantitatively high accuracy in a variety of molecular simulation applications. However, evaluation of three-body potentials is computationally costly, generally of O( N 3 ) where N is the number of particles in a system. In this paper, we present a load-balancing workload distribution scheme for calculating three-body interactions by taking advantage of the Graphics Processing Units (GPU) architectures. Perfect load-balancing is achieved if N is not divisible by 3 and nearly perfect load-balancing is obtained if N is divisible by 3. The workload distribution scheme is particularly suitable for the GPU’s Single Instruction Multiple Threads (SIMT) architecture, where particle’s data accessed by threads can be coalesced into efficient memory transactions. We use two potential energy functions with three-body terms, the Axilrod–Teller potential and the Context-based Secondary Structure Potential, as examples to demonstrate the effectiveness of our workload distribution scheme. [ABSTRACT FROM AUTHOR]

Guidance with traditional trajectory correction scheme usually starts from the trajectory apex time to reduce drag penalties early in flight; however, this method cannot get the max trajectory correction capability of canards according to our analysis. This paper presents an optimized trajectory correction scheme by taking different control phases of canards in ballistic ascending segment and ballistic descending segment. Simulation indicates that the optimized trajectory correction can improve the trajectory correction capability greatly. The result of an example trajectory and Monte Carlo simulations with the predictive guidance law and the trajectory tracking guidance law testifies the effectiveness of the optimized trajectory correction scheme. [ABSTRACT FROM AUTHOR]

The first-order Lax-Friedrichs (LF) scheme is commonly used in conjunction with other schemes to achieve monotone and stable properties with lower numerical diffusion. Nevertheless, the LF scheme and the schemes devised based on it, for example, the first-order centered (FORCE) and the slope-limited centered (SLIC) schemes, cannot achieve a time-step-independence solution due to the excessive numerical diffusion at a small time step. In this work, two time-step-convergence improved schemes, the C-FORCE and C-SLIC schemes, are proposed to resolve this problem. The performance of the proposed schemes is validated in solving the one-layer and two-layer shallow-water equations, verifying their capabilities in attaining time-step-independence solutions and showing robustness of them in resolving discontinuities with high-resolution. [ABSTRACT FROM AUTHOR]

A novel control scheme is proposed to improve the yaw stability of a tractor semitrailer vehicle in critical situations. The control scheme is a two-layer structure consisting of an upper yaw moment controller and a lower brake force distributor. The tractor and the trailer are, respectively, stabilized by two independent fuzzy logic based yaw moment controllers. The controllers for the tractor and the trailer are, respectively, designed to track the reference yaw rate of the tractor and the hitch angle between the tractor and the trailer while considering the variation of the hitch angular rate at the same time. The corrective yaw moments determined by the corresponding upper fuzzy yaw moment controllers are realized by active wheel braking. The performance of the proposed control scheme is evaluated by simulations on a nonlinear vehicle model. The results demonstrate that the proposed control scheme is robust and effective in stabilizing the severe instabilities such as jackknife and trailer oscillation in the chosen simulation scenarios. It is believed that this control scheme is robust to the variation of road adhesion conditions. [ABSTRACT FROM AUTHOR]

Since the censored characteristics are unmonitored effectively in the manufacturing process, the produced product tends to have an unexpected high infant failure rate. Thus, this paper analyzes the associated relationship between product reliability and censored quality characteristics in manufacturing process firstly, and the dynamic and universal control demands for censored characteristics are presented. In view that traditional CEV-based control charts are usually confined to some specific types when dealing with censored characteristics, which greatly restrict the wide application of censored control charts in the high-quality manufacturing process, the convergent CEV technique based on the principle of asymptotic reduction is proposed to be better applied in the analysis of censored characteristics. And novel design procedures and simple but practical performance indicator in the form of the most dangerous alarm distance for censored characteristics of Weibull distribution are put forward. Finally, the validity of the proposed method is verified by a case study of monitoring a censored characteristic relative to lifetime of some aeronautical bearings, and the result proves that the sensitivity of the proposed control chart increased 79.96% compared to traditional CEV chart and is proved to be applicable to monitoring mixed censored characteristics affecting product reliability in manufacturing process. [ABSTRACT FROM AUTHOR]

Like all software systems, databases are subject to evolution as time passes. The impact of this evolution can be vast as a change to the schema of a database can affect the syntactic correctness and the semantic validity of all the surrounding applications. In this paper, we have performed a thorough, large-scale study on the evolution of databases that are part of larger open source projects, publicly available through open source repositories. Lehman׳s laws of software evolution, a well-established set of observations on how the typical software systems evolve (matured during the last forty years), has served as our guide towards providing insights on the mechanisms that govern schema evolution. Much like software systems, we found that schemata expand over time, under a stabilization mechanism that constraints uncontrolled expansion with perfective maintenance. At the same time, unlike typical software systems, the growth is typically low, with long periods of calmness interrupted by bursts of maintenance and a surprising lack of complexity increase. [ABSTRACT FROM AUTHOR]

Because the static cloud platform cannot satisfy the diversity of mobile Internet service and inefficient data mining problems, we presented a reliable and efficient data mining cloud platform construction scheme based on the mobile Internet service opportunistic driving and application perception. In this scheme, first of all data selection mechanism was established based on mobile Internet service opportunistic drive. Secondly, through the cloud platform different cloud and channel aware, nonlinear mapping from the service to a data set of proposed perceptual model is applied. Finally, on the basis of the driving characteristics and extraction of perceptual features, the cloud platform would be constructed through the service opportunities of mobile Internet applications, which could provide robust and efficient data mining services. The experimental results show that the proposed mechanism, compared to the cloud platform based on distributed data mining, has obvious advantages in system running time, memory usage, and data clustering required time, as well as average clustering quality. [ABSTRACT FROM AUTHOR]

The main interest of this paper is to illustrate a new representation of the Principal Component Analysis (PCA) for fault detection under a Conditional Gaussian Network (CGN), a special case of Bayesian networks. PCA and its associated quadratic statistics such as T 2 and SPE are integrated under a sole CGN. The proposed framework projects a new observation into an orthogonal space and gives probabilities on the state of the system. It could do so even when some data in the sample test are missing. This paper also gives the probabilities thresholds to use in order to match quadratic statistics decisions. The proposed network is validated and compared to the standard PCA scheme for fault detection on the Tennessee Eastman Process and the Hot Forming Process. [ABSTRACT FROM AUTHOR]

This paper addresses the data persistence problem in wireless sensor networks (WSNs) where static sinks are not present and the sensed data have to be temporarily but resiliently stored in the network. Based on the observation that sensor readings are correlated, we propose compressive data persistence (CDP) scheme that makes use of the compressive sensing (CS) theory. Each sensor node independently computes and stores a random projection of the sensed data, such that a mobile sink can recover the data with high probability after visiting a small and random portion of the network. As a prerequisite of distributed CS encoding, sensor readings from all nodes are disseminated within the network through random walk. Therefore, the CS measurement matrix depends heavily on how the random walk is performed. In this paper, we present an in-depth analysis on the interplay between random walk parameters and sensing data characteristics, and derive the conditions in successful CS data recovery. In addition, we discover that there is a trade-off between the number of random walk instances and steps in order to achieve the required data persistence performance. Experiments using real sensor data verify that the proposed CDP scheme achieves much lower decoding ratio than the state-of-the-art Fountain code based schemes or the decentralized erasure codes based schemes, and demonstrate that there exist energy-optimized random walk parameters for CDP. [ABSTRACT FROM AUTHOR]

It is well known that the Internet application of cloud services may be affected by the inefficiency of cloud computing and inaccurate evaluation of quality of experience (QoE) seriously. In our paper, based on construction algorithms of cooperative cognitive cloud platform and optimization algorithm of opportunities weight particle swarm clustering, the QoE guarantee mechanism was proposed. The mechanism, through the sending users of requests and the cognitive neighbor users’ cooperation, combined the cooperation of subcloud platforms and constructed the optimal cloud platform with the different service. At the same time, the particle swarm optimization algorithm could be enhanced dynamically according to all kinds of opportunity request weight, which could optimize the cooperative cognitive cloud platform. Finally, the QoE guarantee scheme was proposed with the opportunity weight particle swarm optimization algorithm and collaborative cognitive cloud platform. The experimental results show that the proposed mechanism compared is superior to the QoE guarantee scheme based on cooperative cloud and QoE guarantee scheme based on particle swarm optimization, compared with optimization fitness and high cloud computing service execution efficiency and high throughput performance advantages. [ABSTRACT FROM AUTHOR]

In this study, a numerical model based on the non-oscillatory and non-free parameter dissipation (NND) finite difference scheme for shallow water wave equations including sediment concentration is established in order to simulate the phenomena for dam-break flow and the development of alluvial plain in an estuary. Some numerical experiments show that the numerical model is feasible and efficient for simulating the phenomena for dam-break flow and the development of alluvial plain in an estuary. [ABSTRACT FROM AUTHOR]

With the popularity of IEEE 802.11 based wireless fidelity (Wi-Fi) portable devices, it becomes increasingly significant to support the mobile users carrying Wi-Fi devices to access the Internet of Things (IoT) so that the communications between the mobile users and the smart objects deployed in the IoT stay uninterrupted when the mobile users are in movement. A scheme using Extended Service Set- (ESS-) based architecture is presented to implement the proxy mobile IPv6 protocol, that is, PMIPv6, for IEEE 802.11 infrastructure Wireless Local Area Networks (WLANs). The key signaling packets together with their time sequences for the mobility management in the proposed scheme are proposed. Moreover, the handoff delay in the proposed scheme is derived, through which the performance of the proposed scheme is analyzed. Numerical analysis indicates that the proposed scheme considerably outperforms the existing scheme that uses the Basic Service Set (BSS) based architecture in terms of handoff delay in the case when the delay between Mobile Access Gateway (MAG) and local mobile anchor (LMA) is relatively large. [ABSTRACT FROM AUTHOR]

Zero-knowledge protocols are often studied through specific problems, like Graph-Isomorphism . In many cases this approach prevents an important level of abstraction and leads to limited results, whereas in fact the constructions apply to a wide variety of problems. We propose to address this issue with a formal framework of non-interactive instance-dependent commitment schemes (NIC). We define NIC in the perfect, statistical, and computational settings, and formally characterize problems admitting NIC in all of these settings. We also prove other useful lemmas such as closure properties. Consequently, results that previously applied only to specific problems are now strengthened by our framework to apply to classes of problems . By providing formal yet intuitive tools, our framework facilitates the construction of zero-knowledge protocols for a wide variety of problems, in various settings, without the need to refer to a specific problem. Our results are unconditional. [ABSTRACT FROM AUTHOR]

A hierarchical Bayesian model is developed to characterize the complex-valued high range resolution (HRR) radar target signal, motivated by the problem of radar automatic target recognition (RATR) robust to low signal-to-noise ratio (SNR) or narrowband interference. Here we assume a sparseness-promoting prior on the complex echoes and a Markov dependency for the location of the dominant scattering center between consecutive HRR signals. The number of the dominant scattering centers can be automatically determined, while the posterior distributions of their complex coefficients and locations can be inferred via such Bayesian model. In the training stage, based on the proposed Bayesian model, the statistical aspect-frame template can be learned for HRR complex training samples from each target-aspect sector under high SNR and without any interference. Considering the low SNR or narrowband interference problem for a test sample, the aspect-frame templates can be updated to make a robust recognition decision for the noised and interfered test sample. Simultaneously, the test sample can be denoised and recovered via the analytically posterior estimation for the reconstruction, which is referred to as the statistical compressive sensing (CS) inversion. In contrast to the traditional CS methods that only utilize the underlying sparse property of a measurement (here a measurement is a test sample), our statistical CS inversion also exploits the statistical information of the training samples, which are under high SNR and without any interference. Therefore, the better recognition and reconstruction performances can be obtained via our method. Efficient inference is performed via variational Bayesian (VB) for the proposed Bayesian model. To validate the formulation, we present our experimental results on the measured HRR dataset, with comparisons to some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In-network data aggregation is a widely used method for collecting data efficiently in wireless sensor networks (WSNs). The authors focus on how to achieve high aggregation efficiency and prolonging networks’ lifetime. Firstly, this paper proposes an adaptive spanning tree algorithm (AST), which can adaptively build and adjust an aggregation spanning tree. Owing to the strategies of random waiting and alternative father nodes, AST can achieve a relatively balanced spanning tree and flexible tree adjustment. Then a redundant aggregation scheme (RAG) is illustrated. In RAG, interior nodes help to forward data for their sibling nodes and thus provide reliable data transmission for WSN. Finally, the simulations demonstrate that (1) AST can prolong the lifetime and (2) RAG makes a better trade-off between storage and aggregation ratio, comparing to other aggregation schemes. [ABSTRACT FROM AUTHOR]

Video transmission is a real challenge for wireless multihop networks with high packet loss rate. This paper proposes a cross layer video transmission scheme which combines the geographic routing in network layer and the short-length Luby transform (LT) codes in transport layer. We first analyze the effect of bit error rate (BER) on the retransmission load and the effect of payload length and LT symbols size on network efficiency. Then, based on the product of the link quality and the distance from destination, we design a routing metric for geographic routing. We further propose a cross layer transmission scheme, which adaptively adjusts payload length to encapsulate short-length LT encoded symbols and selects routes based on the new routing metric. The simulation results show that our cross layer scheme can decrease the decoding overhead and the packet loss rate, while improving the video transmission quality and the network efficiency. [ABSTRACT FROM AUTHOR]