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It is anticipated that a large amount of multicast traffic needs to be supported in future communication networks. The network coding technique proposed recently is promising for establishing multicast connections with a significantly lower bandwidth requirement than that of traditional Steiner-tree-based multicast connections. How to design multicast network topologies with the consideration of efficiently supporting multicast by the network coding technique becomes an important issue now. It is notable, however, that the conventional algorithms for network topology design are mainly unicast-oriented, and they cannot be adopted directly for the efficient topology design of network-coding-based multicast networks by simply treating each multicast as multiple unicasts. In this paper, we consider for the first time the novel topology design problem of network-coding-based multicast networks. Based on the characteristics of multicast and network coding, we first formulate this problem as a mixed-integer nonlinear programming problem, which is NP-hard, and then propose two heuristic algorithms for it. The effectiveness of our heuristics is verified through simulation and comparison with the exhaustive search method. We demonstrate in this paper that, in the topology design of multicast networks, adopting the network coding technique to support multicast transmissions can significantly reduce the overall topology cost as compared to conventional unicast-oriented design and the Steiner-tree-based design. [ABSTRACT FROM AUTHOR]

Reliability of tree-like multicast overlays caused by nodes' abrupt failures is considered as one of the major problems for the Internet application-layer media streaming service [1]. In this paper, we address this problem by designing a distributed and light-weighted protocol named the instantaneous reliability oriented protocol (IRP). Unlike most of existing empirical solutions, we first define the overlay reliability problem formally, and propose a protocol containing a node joining algorithm (IRP-Join), a node preemption algorithm (IRP-Preempt), and a node switching algorithm (IRP-Switch) for reactively constructing and repairing the overlay, as well as proactively maintaining the overlay. With the formal problem presentation, we set up a paradigm for solving the overlay reliability problem by theoretically proving the effectiveness of our algorithms. Moreover, by comparing IRP with existing solutions via simulation-based experiments and real-world deployment, we show that IRP achieves a better reliability, while incurs fewer structural adjustments on the multicast overlay, thus, providing a superior overall performance. [ABSTRACT FROM AUTHOR]

Consistent hashing-based DHT networks have an inherent load balancing problem. The problem becomes more severe in heterogeneous networks with nonuniform and time-varying popular files. Existing DHT load balancing algorithms are mainly focused on the issues caused by node heterogeneity. To deal with skewed lookups, this paper presents an elastic routing table (EAT) mechanism for query load balancing, based on the observation that high-degree nodes tend to receive more traffic load. The mechanism allows each node to have a routing table of variable size corresponding to node capacities. The indegree and outdegree of the routing table can also be adjusted dynamically in response to the change of file popularity and network churn. Theoretical analysis proves that the routing table degree is bounded. The EAT mechanism facilitates locality-aware randomized query forwarding to further improve lookup efficiency. By relating query forwarding to a supermarket customer service model, we prove that a two-way randomized query forwarding policy should lead to an exponential improvement in query processing time over random walking. Simulation results demonstrate the effectiveness of the EAT mechanism and its related query forwarding policy for congestion and query load balancing. In comparison with existing "virtual-server"-based load balancing algorithms and other routing table control approaches, the EAT-based congestion control protocol yields significant improvement in query lookup efficiency. [ABSTRACT FROM AUTHOR]

Abstract-In this paper,we present a methodology to develop efficient and deadlock-free routing algorithms for Network-on-Chip (NoC) platforms that are specialized for an application or a set of concurrent applications. The proposed methodology,called the Application- Specific Routing Algorithm (APSRA),exploits the application-specific information regarding pairs of cores that communicate and other pairs that never communicate in the NoC platform to maximize communication adaptivity and performance. The methodology also exploits the known information regarding concurrency/nonconcurrency of communication transactions among cores for the same purpose. The methodology does not require virtual channels to guarantee deadlock freedom. We demonstrate,through analysis of adaptivity and simulation-based evaluation of latency and throughput,that algorithms produced by the proposed methodology give significantly higher performance as compared to other deadlock-free algorithms for both homogeneous and heterogeneous 2D mesh topology NoC systems. Since the APSRA methodology is topology agnostic,the most appropriate general implementation of the routing function within the router is using a table. A table-based implementation of the router is costlier as compared to an algorithm-based implementation. We also propose a technique to compress the routing table in a mesh topology NoC to very small sizes with very little negative effect on routing adaptivity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the theoretical aspects of the nonuniform node distribution strategy used to mitigate the energy hole problem in wireless sensor networks (WSNs). We conclude that in a circular multihop sensor network (modeled as concentric coronas) with nonuniform node distribution and constant data reporting, the unbalanced energy depletion among all the nodes in the network is unavoidable. Even if the nodes in the inner coronas of the network have used up their energy simultaneously, the ones in the outermost corona may still have unused energy. This is due to the intrinsic many-to-one traffic pattern of WSNs. Nevertheless, nearly balanced energy depletion in the network is possible if the number of nodes increases in geometric progression from the outer coronas to the inner ones except the outermost one. Based on the analysis, we propose a novel nonuniform node distribution strategy to achieve nearly balanced energy depletion in the network. We regulate the number of nodes in each corona and derive the ratio between the node densities in the adjacent (i + 1)th and ith coronas by the strategy. Finally, we propose q-Switch Routing, a distributed shortest path routing algorithm tailored for the proposed nonuniform node distribution strategy. Extensive simulations have been performed to validate the analysis. [ABSTRACT FROM AUTHOR]

The localization of sensor nodes is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from GPS devices or by virtue of being manually placed. In this paper, we propose a distributed method to localization of sensor nodes using a single moving beacon, where sensor nodes compute their position estimate based on the range-free technique. Two parameters are critical to the location accuracy of sensor nodes: the radio transmission range of the beacon and how often the beacon broadcasts its position. Theoretical analysis shows that these two parameters determine the upper bound of the estimation error when the traverse route of the beacon is a straight line. We extend the position estimate when the traverse route of the beacon is randomly chosen in a real-world situation, where the radio irregularity might cause a node to miss some crucial coordinate information from the beacon. We further point out that the movement pattern of the beacon plays a pivotal role in the localization task for sensors. To minimize estimation errors, sensor nodes can carry out a variety of algorithms in accordance with the movement of the beacon. Simulation results compare variants of the distributed method in a variety of testing environments. Real experiments show that the proposed method is feasible and can estimate the location of sensor nodes accurately, given a single moving beacon. [ABSTRACT FROM AUTHOR]

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in the location data of tracked objects, this paper studies precision-constrained approximate queries that trade answer precision for energy efficiency. We develop an Energy-conserving Approximate StoragE (EASE) scheme to efficiently answer approximate location queries by keeping error-bounded imprecise location data at some designated storage node. The data impreciseness is captured by a system parameter called the approximation radius. We derive the optimal setting of the approximation radius for our storage scheme based on the mobility pattern, and devise an adaptive algorithm to adjust the setting when the mobility pattern is not available a priori or is dynamically changing. Simulation experiments are conducted to validate our theoretical analysis of the optimal approximation setting. The simulation results show that the proposed EASE scheme reduces the network traffic from a conventional approach by up to 96%, and in most cases, prolongs the network lifetime by a factor of 2-5. [ABSTRACT FROM AUTHOR]

This paper proposes a novel and simple adaptive control algorithm for the effective delay control and resource utilization of end host multicast (EMcast) when the traffic load becomes heavy in a multigroup network with real-time flows constrained by (σ, ρ) regulators. The control algorithm is implemented at the overlay networks and provides more regulations through a novel (σ, ρ, λ) regulator at each group end host who suffers from heavy input traffic. To our knowledge, it is the first work to incorporate traffic regulators into the end host multicast to control heavy traffic output. Our further contributions include a theoretical analysis and a set of results. We prove the existence and calculate the value of the rate threshold ρ* such that for a given set of K groups, when the average rate of traffic entering the group end hosts ρ¯ > ρ*, the ratio of the worst-case multicast delay bound of the proposed (σ, ρ, λ) regulator over the traditional (σ, ρ) regulator is O((Multiple line equation(s) cannot be represented in ASCII text)) for any integer n. We also prove the efficiency of the novel algorithm and regulator in decreasing worst-case delays by conducting computer simulations. [ABSTRACT FROM AUTHOR]

The efficiency of sensor networks depends on the coverage of the monitoring area. Although, in general, a sufficient number of sensors are used to ensure a certain degree of redundancy in coverage, a good sensor deployment is still necessary to balance the workload of sensors. In a sensor network with locomotion facilities, sensors can move around to self-deploy. The movement-assisted sensor deployment deals with moving sensors from an initial unbalanced state to a balanced state. Therefore, various optimization problems can be defined to minimize different parameters, including total moving distance, total number of moves, communication/computation cost, and convergence rate. In this paper, we first propose a Hungarian-algorithm-based optimal solution, which is centralized. Then, a localized Scan-based Movement-Assisted sensor deployment method (SMART) and several variations of it that use scan and dimension exchange to achieve a balanced state are proposed. An extended SMART is developed to address a unique problem called communication holes in sensor networks. Extensive simulations have been done to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an efficient Quality of Service (QoS)-constrained data aggregation and processing approach for distributed wireless sensor networks is investigated and analyzed. One of the key features of the proposed approach is that the task QoS requirements are taken into account to determine when and where to perform the aggregation in a distributed fashion, based on the availability of local only information. Data aggregation is performed on the fly at intermediate sensor nodes, while at the same time the end-to-end latency constraints are satisfied. Furthermore, a localized adaptive data collection algorithm performed at the source nodes is developed that balances the design tradeoffs of delay, measurement accuracy, and buffer overflow, for given QoS requirements. The performance of the proposed approach is analyzed and evaluated, through modeling and simulation, under different data aggregation scenarios and traffic loads. The impact of several design parameters and tradeoffs on various critical network and application related performance metrics, such as energy efficiency, network lifetime, end-to-end latency, and data loss are also evaluated and discussed. [ABSTRACT FROM AUTHOR]

Divisible load applications occur in many fields of science and engineering and can be easily parallelized in a master-worker fashion, but pose several scheduling challenges. While a number of approaches have been proposed that allocate toad to workers in a single round, using multiple rounds improves overlap of computation with communication. Unfortunately, multiround algorithms are difficult to analyze and have thus received only limited attention. In this paper, we answer three open questions in the multiround divisible load scheduling area: 1) how to account for Iatencies, 2) how to account for heterogeneous platforms, and 3) how many rounds should be used. To answer 1), we derive the first closed-form optimal schedule for a homogeneous platform with both computation and communication latencies, for a given number of rounds. To answer 2) and 3), we present a novel algorithm, UMR. We evaluate UMR in a variety of realistic scenarios. [ABSTRACT FROM AUTHOR]

An increasing number of distributed real-time systems face the critical challenge of providing quality of service guarantees In open and unpredictable environments. In particular, such systems often need to enforce utilization bounds on multiple processors in order to avoid overload and meet end-to-end deadlines even when task execution times are unpredictable. While recent feedback control real-time scheduling algorithms have shown promise, they cannot handle the common end-to-end task model where each task is comprised of a chain of subtasks distributed on multiple processors. This paper presents the End-to-end Utilization CONtrol (EUCON) algorithm that adaptively maintains desired CPU utilization through performance feedbacks loops. EUCON is based on a model predictive control approach that models utilization control on a distributed platform as a multivariable constrained optimization problem. A multi-input-multi-output model predictive controller is designed based on a difference equation model that describes the dynamic behavior of distributed real-time systems. Both control theoretic analysis and simulations demonstrate that EUCON can provide robust utilization guarantees when task execution times deviate from estimation or vary significantly at runtime. [ABSTRACT FROM AUTHOR]

Self-pruning is an effective scheme for efficient broadcasting in ad hoc wireless networks. In a self-pruning broadcast protocol, a node may not forward a broadcast packet if a certain self-pruning condition is satisfied based on the neighborhood information. In a static network with an ideal MAC layer, only a subset of nodes forward the broadcast packet and still guarantee the complete network delivery. Various protocols have been proposed with different self-pruning conditions. Recently, a generic self-pruning protocol was proposed by Wu and Dai [21], which combines the strength of previous conditions and is more effective. In this paper, we first propose an enhanced version of the generic protocol, which is more elegant in interpreting existing protocols and has a simpler correctness proof. Then, we evaluate the performance of the family of self-pruning protocols under various network situations with ns2. The objective is to observe the efficiency and reliability of these protocols as a function of network density, congestion, and mobility, and provide a guideline of implementation in the "real world." Our performance analysis reveals that the protocol reliability is barely affected by packet collision. However, most self-pruning protocols suffer from low delivery ratio in highly mobile networks. We further explore various techniques that improve the delivery ratio and show that both high efficiency and reliability can be achieved in highly mobile networks. [ABSTRACT FROM AUTHOR]

RFID tag identification is a crucial problem in UHF RFID systems. Traditional tag identification algorithms can be classified into two categories, ALOHA-based and tree-based. Both of them are inefficient due to the incidental high coordination cost. In this paper, we bring CSMA into UHF RFID systems to enhance tag read rate by reducing coordination cost. However, it is not straightforward due to the simple hardware design of passive RFID tags, which is unable to sense the transmissions or collisions of other tags. To tackle this challenge, we propose receiver-based CSMA (RCSMA) in this paper. In RCSMA, the reader notifies the tags channel condition. According to different sensing results of reader's notifications, the tags take corresponding actions, e.g., random back off. RCSMA does not require special RFID tag hardware design. An absorbing Markov chain model is presented to analyze the performance of RCSMA and shown to be consistent with the simulation results. Compared with optimized ALOHA-based algorithms and optimized tree-based algorithms, RCSMA can enhance the tag read rate by 30-70 percent under different reader and tag data rates. [ABSTRACT FROM AUTHOR]

Recently, utility Grids have emerged as a new model of service provisioning in heterogeneous distributed systems. In this model, users negotiate with service providers on their required Quality of Service and on the corresponding price to reach a Service Level Agreement. One of the most challenging problems in utility Grids is workflow scheduling, i.e., the problem of satisfying the QoS of the users as well as minimizing the cost of workflow execution. In this paper, we propose a new QoS-based workflow scheduling algorithm based on a novel concept called Partial Critical Paths (PCP), that tries to minimize the cost of workflow execution while meeting a user-defined deadline. The PCP algorithm has two phases: in the deadline distribution phase it recursively assigns subdeadlines to the tasks on the partial critical paths ending at previously assigned tasks, and in the planning phase it assigns the cheapest service to each task while meeting its subdeadline. The simulation results show that the performance of the PCP algorithm is very promising. [ABSTRACT FROM AUTHOR]

This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation (IR)-based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU-based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multithreaded parallel programming makes the entire implementation highly transparent, scalable, and efficient. Several large test systems are used for the simulation with a maximum size of 9,984 buses and 2,560 synchronous generators all modeled in detail resulting in matrices that are larger than 20\,000\times 20\,000. [ABSTRACT FROM AUTHOR]

Maintaining a given level of data redundancy is a fundamental requirement of peer-to-peer (P2P) storage systems—to ensure desired data availability, additional replicas must be created when peers fail. Since the majority of failures in P2P networks are transient (i.e., peers return with data intact), an intelligent system can reduce significant replication costs by not replicating data following transient failures. Reliably distinguishing permanent and transient failures, however, is a challenging task, because peers are unresponsive to probes in both cases. In this paper, we propose Protector, an algorithm that enables efficient replication policies by estimating the number of “remaining replicas” for each object, including those temporarily unavailable due to transient failures. Protector dramatically improves detection accuracy by exploiting two opportunities. First, it leverages failure patterns to predict the likelihood that a peer (and the data it hosts) has permanently failed given its current downtime. Second, it detects replication level across groups of replicas (or fragments), thereby balancing false positives for some peers against false negatives for others. Extensive simulations based on both synthetic and real traces show that Protector closely approximates the performance of a perfect “oracle” failure detector, and significantly outperforms time-out-based detectors using a wide range of parameters. Finally, we design, implement and deploy an efficient P2P storage system called AmazingStore by combining Protector with structured P2P overlays. Our experience proves that Protector enables efficient long-term data maintenance in P2P storage systems. [ABSTRACT FROM PUBLISHER]

In this paper, a diverse range of routing algorithms is classified into a new family of routings called zone-ordered label-based routing algorithms. The proposed classification is based on three common steps (factors) for generating such routings, namely, graph labeling, deadlock-free zones, and zone ordering. The main goal of this classification is to define several new routing concepts and streamline the knowledge on routing algorithms. Following the classification, a novel methodology is proposed to generate routing algorithms for irregular networks. The methodology uses the three mentioned steps to generate deadlock-free routings. Consequently, the methodology-based routings fall into the category of zone-ordered label-based routings. However, the graph labeling method (first step) used in the methodology is based on multiple spanning tree construction on the network. The simulation results show that constructing further spanning trees may result in routing algorithm with better performance. [ABSTRACT FROM AUTHOR]

Oil and gas companies trust Reverse Time Migration (RTM), the most advanced seismic imaging technique, with crucial decisions on drilling investments. The economic value of the oil reserves that require RTM to be localized is in the order of 10^13 dollars. But RTM requires vast computational power, which somewhat hindered its practical success. Although, accelerator-based architectures deliver enormous computational power, little attention has been devoted to assess the RTM implementations effort. The aim of this paper is to identify the major limitations imposed by different accelerators during RTM implementations, and potential bottlenecks regarding architecture features. Moreover, we suggest a wish list, that from our experience, should be included as features in the next generation of accelerators, to cope with the requirements of applications like RTM. We present an RTM algorithm mapping to the IBM Cell/B.E., NVIDIA Tesla and an FPGA platform modeled after the Convey HC-1. All three implementations outperform a traditional processor (Intel Harpertown) in terms of performance (10x), but at the cost of huge development effort, mainly due to immature development frameworks and lack of well-suited programming models. These results show that accelerators are well positioned platforms for this kind of workload. Due to the fact that our RTM implementation is based on an explicit high order finite difference scheme, some of the conclusions of this work can be extrapolated to applications with similar numerical scheme, for instance, magneto-hydrodynamics or atmospheric flow simulations. [ABSTRACT FROM AUTHOR]

Data aggregation is a key functionality in wireless sensor networks (WSNs). This paper focuses on data aggregation scheduling problem to minimize the delay (or latency). We propose an efficient distributed algorithm that produces a collision-free schedule for data aggregation in WSNs. We theoretically prove that the delay of the aggregation schedule generated by our algorithm is at most 16R+\Delta -14 time slots. Here, R is the network radius and \Delta is the maximum node degree in the communication graph of the original network. Our algorithm significantly improves the previously known best data aggregation algorithm with an upper bound of delay of 24D+6\Delta +16 time slots, where D is the network diameter (note that D can be as large as 2R). We conduct extensive simulations to study the practical performances of our proposed data aggregation algorithm. Our simulation results corroborate our theoretical results and show that our algorithms perform better in practice. We prove that the overall lower bound of delay for data aggregation under any interference model is max \\log n, R\, where n is the network size. We provide an example to show that the lower bound is (approximately) tight under the protocol interference model when r_I=r, where r_I is the interference range and r is the transmission range. We also derive the lower bound of delay under the protocol interference model when r