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Network research generally requires a simulation or emulation environment to test protocol implementations, to evaluate the performance of a scheme or a system, and to study complicated and highly varying network operations. For large network simulation, simulators will consume a large amount of time and memory, and its result is largely based on some modeling assumptions that may not hold in the real world. Emulators are difficult to scale for large network emulation because of the high cost of equipment if a one-to-one mapping scheme is employed. Otherwise, the target network has to be abstracted to a single router modeled with some performance metrics. In this paper, we present a distributed IP network emulator cluster EMPOWER, which not only can be used to emulate a large network with a limited number of commodity computers, but also can generate user-defined arbitrary network conditions and traffic dynamics at packet level for specific test scenarios. EMPOWER is highly scalable in that each emulator node could be configured to emulate multiple network nodes, and the increment of the number of emulator nodes does not affect emulation validity. Some significant research issues such as network mapping and mobile wireless network emulation are discussed and addressed. Preliminary emulation results show that EMPOWER is capable of assisting the study of both wireline and wireless network protocols and applications. [ABSTRACT FROM AUTHOR]

Presents an incremental design of scalable interconnection networks in multicomputer systems using basic building blocks. Consideration of both network topologies and routing algorithms; Use of worm-hole-routed small-scale two-dimensional meshes as basic building blocks; Minimum requirement to expand networks; Adoption of original algorithms designed from turn model.

Explores the potential of cut-through switching approach in supporting high-speed local area networks. Necessity of adaptive tail-routing in providing consistent interconnection among cut-through switches; Evaluation of the approach through simulation experiments; Description and characterization of the Eulerian tail.

Presents a study focusing on the use of switch-based network architectures for constructing scalable parallel computers (SPCs). Metric used to evaluate a network; Features of SPCs; Outcome of a comparison between three unidirectional cubes; Examination of network traffic patterns.

Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either "connected" or "disconnected." These approaches are called connectivity-based topology control. In real environments, however, there are many intermittently connected wireless links called lossy links. Taking a succeeded lossy link as an advantage, we are able to construct more energy-efficient topologies. Toward this end, we propose a novel opportunity-based topology control. We show that opportunity-based topology control is a problem of NP-hard. To address this problem in a practical way, we design a fully distributed algorithm called CONREAP based on reliability theory. We prove that CONREAP has a guaranteed performance. The worst running time is O(∣E∣), where E is the link set of the original topology, and the space requirement for individual nodes is O(d), where d is the node degree. To evaluate the performance of CONREAP, we design and implement a prototype system consisting of 50 Berkeley Mica2 motes. We also conducted comprehensive simulations. Experimental results show that compared with the connectivity-based topology control algorithms, CONREAP can improve the energy efficiency of a network up to six times. [ABSTRACT FROM AUTHOR]

A sustainable market-like computational grid has two characteristics: it must allow resource providers and resource consumers to make autonomous scheduling decisions, and both parties of providers and consumers must have sufficient incentives to stay and play in the market. In this paper, we formulate this intuition of optimizing incentives for both parties as a dual-objective scheduling problem. The two objectives identified are to maximize the success rate of job execution and to minimize fairness deviation among resources. The challenge is to develop a grid scheduling scheme that enables individual participants to make autonomous decisions while producing a desirable emergent property in the grid system; that is, the two systemwide objectives are achieved simultaneously. We present an incentive-based scheduling scheme, which utilizes a peer-to-peer decentralized scheduling framework, a set of local heuristic algorithms, and three market instruments of job announcement, price, and competition degree. The performance of this scheme is evaluated via extensive simulation using synthetic and real workloads. The results show that our approach outperforms other scheduling schemes in optimizing incentives for both consumers and providers, leading to highly successful job execution and fair profit allocation. [ABSTRACT FROM AUTHOR]

The Peer-to-Peer (P2P) model, being widely adopted in today's Internet computing, suffers from the problem of topology mismatch between the overlay networks and the underlying physical network. Traditional topology optimization techniques identify physically closer nodes to connect as overlay neighbors, but could significantly shrink the search scope. Recent efforts have been made to address the mismatch problem without sacrificing the search scope, but they either need time synchronization among peers or have a low convergent speed. In this paper, we propose a scalable bipartite overlay (SBO) scheme to optimize the overlay topology by identifying and replacing the mismatched connections. In SBO, we employ an efficient strategy for distributing optimization tasks in peers with different colors. We conducted comprehensive simulations to evaluate this design. The results show that SBO achieves approximately 85 percent of reduction on traffic cost and about 60 percent of reduction on query response time. Our comparisons with previous approaches to address the topology mismatch problem have shown that SBO can achieve a fast convergent speed, without the need of time synchronization among peers. [ABSTRACT FROM AUTHOR]

Multicast is a crucial routine operation for vehicular networks, which underpins important functions such as message dissemination and group coordination. As vehicles may distribute over a vast area, the number of vehicles in a given region can be limited which results in sparse node distribution in part of the vehicular network. This poses several great challenges for efficient multicast, such as network disconnection, scarce communication opportunities and mobility uncertainty. Existing multicast schemes proposed for vehicular networks typically maintain a forwarding structure assuming the vehicles have a high density and move at low speed while these assumptions are often invalid in a practical vehicular network. As more and more vehicles are equipped with GPS enabled navigation systems, the trajectories of vehicles are becoming increasingly available. In this work, we propose an approach called TMC to exploit vehicle trajectories for efficient multicast in vehicular networks. The novelty of TMC includes a message forwarding metric that characterizes the capability of a vehicle to forward a given message to destination nodes, and a method of predicting the chance of inter-vehicle encounter between two vehicles based only on their trajectories without accurate timing information. TMC is designed to be a distributed approach. Vehicles make message forwarding decisions based on vehicle trajectories shared through inter-vehicle exchanges without the need of central information management. We have performed extensive simulations based on real vehicular GPS traces and compared our proposed TMC scheme with other existing approaches. The performance results demonstrate that our approach can achieve a delivery ratio close to that of the flooding-based approach while the cost is reduced by over 80 percent. [ABSTRACT FROM PUBLISHER]

Geocast in vehicular networks aims to deliver a message to a target geographical region, which is useful for many applications such as geographic advertising. This is a highly challenging task in vehicular network environments due to the rare encounter opportunities and uncertainty caused by vehicular mobility. As more vehicles are equipped with on-board navigation systems, vehicle trajectories are ready for exploitation. We observe that a vehicle has a higher capability of delivering a message to the target region if its own future trajectory or trajectories of those vehicles to be encountered overlap the target region. Motivated by this observation, we develop a message forwarding metric, called coverage capability, to characterize the capability of a vehicle to successfully geocast the message. When calculating the coverage capability, we are facing the major challenge raised by the absence of accurate vehicle arrival time. Through an empirical study using real vehicular GPS traces of 2,600 taxis, we verify that the travel time of a vehicle, which is modeled as a random variable, follows the Gamma distribution. The travel time modeling helps us to make accurate predictions for inter-vehicle encounters. We perform extensive trace-driven simulations and the results show that our approach achieves 37.4 percent higher delivery ratio and 43.1 percent lower transmission overhead comparing with GPSR which is a representative geographic routing protocol. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) based technologies play an important role in indoor localization, since Radio Signal Strength (RSS) can be easily measured by various wireless devices without additional cost. Among these, radio map based technologies (also referred as fingerprinting technologies) are attractive due to high accuracy and easy deployment. However, these technologies have not been extensively applied on real environment for two fatal limitations. First, it is hard to localize multiple objects. When the number of target objects is unknown, constructing a radio map of multiple objects is almost impossible. Second, environment changes will generate different multipath signals and severely disturb the RSS measurement, making laborious retraining inevitable. Motivated by these, in this paper, we propose a novel approach, called Line-of-sight radio map matching, which only reserves the LOS signal among nodes. It leverages frequency diversity to eliminate the multipath behavior, making RSS more reliable than before. We implement our system MODLoc based on TelosB sensor nodes and commercial 802.11 NICs with Channel State Information (CSI) as well. Through extensive experiments, it shows that the accuracy does not decrease when localizing multiple targets in a dynamic environment. Our work outperforms the traditional methods by about 60 percent. More importantly, no calibration is required in such environment. Furthermore, our approach presents attractive flexibility, making it more appropriate for general RF-based localization studies than just the radio map based localization. [ABSTRACT FROM AUTHOR]

In traditional radio-based localization methods, the target object has to carry a transmitter (e.g., active RFID), a receiver (e.g., 802.11\times detector), or a transceiver (e.g., sensor node). However, in some applications, such as safe guard systems, it is not possible to meet this precondition. In this paper, we propose a model of signal dynamics to allow the tracking of a transceiver-free object. Based on radio signal strength indicator (RSSI), which is readily available in wireless communication, three centralized tracking algorithms, and one distributed tracking algorithm are proposed to eliminate noise behaviors and improve accuracy. The midpoint and intersection algorithms can be applied to track a single object without calibration, while the best-cover algorithm has higher tracking accuracy but requires calibration. The probabilistic cover algorithm is based on distributed dynamic clustering. It can dramatically improve the localization accuracy when multiple objects are present. Our experimental test-bed is a grid sensor array based on MICA2 sensor nodes. The experimental results show that the localization accuracy for single object can reach about 0.8 m and for multiple objects is about 1 m. [ABSTRACT FROM AUTHOR]

Improving channel utilization is a well-known issue in wireless networks. In traditional point-to-point wireless communication, significant efforts had been made by the existing studies on enhancing the utilization of the channel access time. However, in the emerging wireless network using MU-MIMO, considering only the time domain in channel utilization is not sufficient. As multiple transmitters are allowed to transmit packets simultaneously to the same AP, allowing more antennas at AP would lead to higher channel utilization. Thus, the channel utilization in MU-MIMO should consider both time and spatial domains, i.e., the channel access time and the antenna usage, which have not been considered in the existing methods. In this paper, we point out that the fundamental problem is lacking of the antenna information of contention nodes in channel contention. To address this issue, we propose a new MAC-PHY architecture design, CUTS, to allow distributed nodes effectively contend for the channel and utilize the channel in both domains. Particularly, CUTS adopts interference nulling to attach the antenna information in channel contention. Meanwhile, techniques such as channel contention in frequency domain and ACK in frequency domain using self-jamming are adopted. Through the software defined radio-based real experiments and extensive simulations, we demonstrate the feasibility of our design and illustrate that CUTS provides better channel utilization with the gain over IEEE 802.11 reaching up to 470 percent. [ABSTRACT FROM AUTHOR]

In this paper, we first propose a very interesting and practical problem, pattern matching in a distributed mobile environment. Pattern matching is a well-known problem and extensive research has been conducted for performing effective and efficient search. However, previous proposed approaches assume that data are centrally stored, which is not the case in a mobile environment (e.g., mobile phone networks), where one person's pattern could be separately stored in a number of different stations, and such a local pattern is incomplete compared with the global pattern. A simple solution to pattern matching over a mobile environment is to collect all the data distributed in base stations to a data center and conduct pattern matching at the data center afterwards. Clearly, such a simple solution will raise huge amount of communication traffic, which could cause the communication bottleneck brought by the limited wireless bandwidth to be even worse. Therefore, a communication efficient and search effective solution is necessary. In our work, we present a novel solution which is based on our well-designed weighted bloom filter (WBF), called, D istributed Incomplete pattern matching ( DI-matching), to find target patterns over a distributed mobile environment. Specifically, to save communication cost and ensure pattern matching in distributed incomplete patterns, we use WBF to encode a query pattern and disseminate the encoded data to each base station. Each base station conducts a local pattern search according to the received WBF. Only qualified IDs and corresponding weights in each base station are sent to the data center for aggregation and verification. Through non-trivial theoretical analysis and extensive empirical experiments on a real city-scale mobile networks data set, we demonstrate the effectiveness and efficiency of our proposed solutions. [ABSTRACT FROM PUBLISHER]

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. WiFi-based indoor localization has been attractive due to its open access and low cost properties. However, the distance estimation based on received signal strength indicator (RSSI) is easily affected by the temporal and spatial variance due to the multipath effect, which contributes to most of the estimation errors in current systems. In this work, we analyze this effect across the physical layer and account for the undesirable RSSI readings being reported. We explore the frequency diversity of the subcarriers in orthogonal frequency division multiplexing systems and propose a novel approach called FILA, which leverages the channel state information (CSI) to build a propagation model and a fingerprinting system at the receiver. We implement the FILA system on commercial 802.11 NICs, and then evaluate its performance in different typical indoor scenarios. The experimental results show that the accuracy and latency of distance calculation can be significantly enhanced by using CSI. Moreover, FILA can significantly improve the localization accuracy compared with the corresponding RSSI approach. [ABSTRACT FROM AUTHOR]

The growing importance of operations such as identification, location sensing, and object tracking has led to increasing interests in contactless Radio Frequency Identification (RFID) systems. Enjoying the low cost of RFID tags, modern RFID systems tend to be deployed for large-scale mobile objects. Both the theoretical and experimental results suggest that when tags are in large numbers, most existing collision arbitration protocols do not satisfy the scalability and time-efficiency requirements of many applications. To address this problem, we propose Adaptively Splitting-based Arbitration Protocol (ASAP), a scheme that provides efficient RFID identification for both small and large deployment of RFID tags, in terms of time and energy cost. Theoretical analysis and simulation evaluation show that the performance of ASAP is better than most existing collision-arbitration solutions and the time efficiency is close to the theoretically optimal values. [ABSTRACT FROM AUTHOR]

Transceiver-free object tracking is to trace a moving object that does not carry any communication device in an environment with some monitoring nodes predeployed. Among all the tracking technologies, RF-based technology is an emerging research field facing many challenges. Although we proposed the original idea, until now there is no method achieving scalability without sacrificing latency and accuracy. In this paper, we put forward a real-time tracking system RASS, which can achieve this goal and is promising in the applications like the safeguard system. Our basic idea is to divide the tracking field into different areas, with adjacent areas using different communication channels. So, the interference among different areas can be prevented. For each area, three communicating nodes are deployed on the ceiling as a regular triangle to monitor this area. In each triangle area, we use a Support Vector Regression (SVR) model to locate the object. This model simulates the relationship between the signal dynamics caused by the object and the object position. It not only considers the ideal case of signal dynamics caused by the object, but also utilizes their irregular information. As a result, it can reach the tracking accuracy to around 1 m by just using three nodes in a triangle area with 4 m in each side. The experiments show that the tracking latency of the proposed RASS system is bounded by only about 0.26 m. Our system scales well to a large deployment field without sacrificing the latency and accuracy. [ABSTRACT FROM AUTHOR]

Reliable communications are essential for most applications in wireless sensor networks (WSNs). In traditional approaches, the per-hop and end-to-end (E2E) recovery schemes are widely used. These schemes, however, suffer from low E2E success rate and poor energy efficiency in large-scale real environments. Through empirical studies, in this paper we identify three major problems that hinder the efficient and reliable communications. To address these problems, we propose a novel in-middle recovery scheme and realize it by designing and implementing a proliferation routing. Proliferation routing integrates three core technologies, namely, capability-based path finder, a randomized dispersity, and reproduction. Proliferation routing offers great flexibilities for transmissions. It cannot only be applied with any Medium Access Control (MAC) protocols and routing metrics, but also obtains a desired service quality (i.e., transmission success rate, energy cost, etc.) by controlling the system parameters. To demonstrate the effectiveness of proliferation routing, we thoroughly analyze its performance. We also conduct performance evaluations through implementation experiments as well as simulations. In a specific experimental setup, proliferation routing can increase the E2E transmission success rate up to 80 percent compared with the well-known hop-based routing and flooding. [ABSTRACT FROM PUBLISHER]

Intelligent transportation systems have become increasingly important for the public transportation in Shanghai. In response, ShanghaiGrid (SG) project aims to provide abundant intelligent transportation services to improve the traffic condition. A challenging service in SG is to accurately locate the positions of moving vehicles in real time. In this paper, we present an innovative scheme, Hierarchical Exponential Region Organization (HERO), to tackle this problem. In SG, the location information of individual vehicles is actively logged in local nodes which are distributed throughout the city. For each vehicle, HERO dynamically maintains an advantageous hierarchy on the overlay network of local nodes to conservatively update the location information only in nearby nodes. By bounding the maximum number of hops the query is routed, HERO guarantees to meet the real-time constraint associated with each vehicle. A small-scale prototype system implementation and extensive simulations based on the real road network and trace data of vehicle movements from Shanghai demonstrate the efficacy of HERO. [ABSTRACT FROM AUTHOR]

By combining an unstructured protocol with a DHT-based global index, hybrid peer-to-peer (P2P) improves search efficiency in terms of query recall and response time. The major challenge in hybrid search is how to estimate the number of peers that can answer a given query. Existing approaches assume that such a number can be directly obtained by computing item popularity. In this work, we show that such an assumption is not always valid, and previous designs cannot distinguish whether items related to a query are distributed in many peers or are in a few peers. To address this issue, we propose QRank, a difficulty-aware hybrid search, which ranks queries by weighting keywords based on term frequency. Using rank values, QRank selects proper search strategies for queries. We conduct comprehensive trace-driven simulations to evaluate this design. Results show that QRank significantly improves the search quality as well as reducing system traffic cost compared with existing approaches. [ABSTRACT FROM AUTHOR]

Most trust models in Peer-to-Peer (P2P) systems are identity based, which means that in order for one peer to trust another, it needs to know the other peer's identity. Hence, there exists an inherent trade-off between trust and anonymity. To the best of our knowledge, there is currently no P2P protocol that provides complete mutual anonymity as well as authentication and trust management. We propose a zero-knowledge authentication scheme called Pseudo Trust (PT), where each peer, instead of using its real identity, generates an unforgeable and verifiable pseudonym using a one-way hash function. A novel authentication scheme based on Zero-Knowledge Proof is designed so that peers can be authenticated without leaking any sensitive information. With the help of PT, most existing identity-based trust management schemes become applicable in mutual anonymous P2P systems. We analyze the security and the anonymity in PT and evaluate its performance using trace-driven simulations and a prototype PT-enabled P2P network. The strengths of our design include the following: 1) no need for a centralized trusted party or Certificate Authority (CA); 2) high scalability and security; 3)low traffic and cryptography processing overheads; and 4) man-in-the-middle-attacks resistance. [ABSTRACT FROM AUTHOR]

In order to provide scalable live streaming services, we propose an Interoverlay Optimization scheme, IOO. Instead of selecting better paths in the same overlay, IOO constructs efficient paths using peers in different overlays so as to 1) improve global resource utilization of peer-to-peer (P2P) streaming networks, 2) assign resources based on their locality and delay, 3) guarantee streaming service quality by using the nearest peers, even when such peers might belong to different overlays, and 4) balance the load among the group (streaming overlay) members. We compare the performance of IOO with existing approaches through trace-driven simulations. Results show that IOO outperforms previous schemes in terms of resource utilization and the quality of service (QoS) of streaming services. The IOO scheme has been implemented in an Internet-based live streaming system, called AnySee. AnySee was successfully released in the summer of 2004 in the China Educational Research Network (CERNET). More than 60,000 users enjoy massive entertainment programs, including TV programs, movies, and academic conferences videos. [ABSTRACT FROM AUTHOR]

Abstract-The involvement of only the necessary users and service providers for service discovery in pervasive computing environments is challenging. Without prudence, users' and service providers' requests or service information, their identities, and their presence information may be sacrificed. We identify that the problem may be as difficult as a chicken-and-egg problem, in which both users and service providers want the other parties to expose sensitive information first. In this paper, we propose a progressive and probabilistic approach to solve the problem. Users and service providers expose partial information in turn and avoid unnecessary exposure if there is any mismatch. Although 1 or 2 bits of information are exchanged in each message, we prove that the process converges and that the false-positive overhead decreases quickly. Experiments and hypothesis tests show that security properties hold. We implemented the approach and the performance measurements show that the approach runs efficiently on PDAs. [ABSTRACT FROM AUTHOR]

Sensor networks have emerged as a promising technology with various applications, where power efficiency is one of the critical requirements. The recent IEEE 802.15.4 standard offers a promising platform for wireless sensor networks. Since each node can act as a coordinator or a device in the IEEE 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. To reduce power consumption, in this paper, we try to construct network topologies with a small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning (SP) is the simplest one with O(1) running time and provides the shortest path to the sink node. Ordinal pruning (OP) can significantly improve SP in terms of power saving with O(n) running time. Layered pruning (LP) is a trade off between the first two pruning algorithms with O(√n) running time and has a slightly higher power consumption than OP. Furthermore, all three algorithms are independent of the physical radio propagation characteristics. Extensive simulations have been performed to verify the effectiveness of the proposed topology control schemes. [ABSTRACT FROM AUTHOR]

Many research activities on Wireless Sensor Networks (WSNs) need detailed performance statistics about protocols, systems, and applications; however, current simulation tools and testbeds lack mechanisms to report these statistics realistically and conveniently. To address this need, we have developed a WSN emulator, VMNet. VMNet emulates networked sensor nodes at the level of CPU clock cycles and executes the binary code of real applications directly. It emulates the radio channel with loss and noise as well as emulates the peripherals in sufficient detail. Moreover, VMNet takes parameter values from the real world and logs detailed runtime information of emulated nodes. Consequently, the application performance, both in response time and in power consumption, is reported realistically in VMNet, as demonstrated by our comparison studies with real sensor networks. [ABSTRACT FROM AUTHOR]

Surveillance is a critical problem for harbor protection, border control or the security of commercial facilities. The effective protection of vast near-coast sea surfaces and busy harbor areas from intrusions of unauthorized marine vessels, such as pirates smugglers or, illegal fishermen is particularly challenging. In this paper, we present an innovative solution for ship intrusion detection. Equipped with three-axis accelerometer sensors, we deploy an experimental Wireless Sensor Network (WSN) on the sea's surface to detect ships. Using signal processing techniques and cooperative signal processing, we can detect any passing ships by distinguishing the ship-generated waves from the ocean waves. We design a three-tier intrusion detection system with which we propose to exploit spatial and temporal correlations of an intrusion to increase detection reliability. We conduct evaluations with real data collected in our initial experiments, and provide quantitative analysis of the detection system, such as the successful detection ratio, detection latency, and an estimation of an intruding vessel's velocity. [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]

Efficient and effective full-text retrieval in unstructured peer-to-peer networks remains a challenge in the research community. First, it is difficult, if not impossible, for unstructured P2P systems to effectively locate items with guaranteed recall. Second, existing schemes to improve search success rate often rely on replicating a large number of item replicas across the wide area network, incurring a large amount of communication and storage costs. In this paper, we propose BloomCast, an efficient and effective full-text retrieval scheme, in unstructured P2P networks. By leveraging a hybrid P2P protocol, BloomCast replicates the items uniformly at random across the P2P networks, achieving a guaranteed recall at a communication cost of O(\sqrtN), where N is the size of the network. Furthermore, by casting Bloom Filters instead of the raw documents across the network, BloomCast significantly reduces the communication and storage costs for replication. We demonstrate the power of BloomCast design through both mathematical proof and comprehensive simulations based on the query logs from a major commercial search engine and NIST TREC WT10G data collection. Results show that BloomCast achieves an average query recall of 91 percent, which outperforms the existing WP algorithm by 18 percent, while BloomCast greatly reduces the search latency for query processing by 57 percent. [ABSTRACT FROM PUBLISHER]

RFID has been gaining popularity due to its variety of applications, such as inventory control and localization. One important issue in RFID system is tag identification. In RFID systems, the tag randomly selects a slot to send a Random Number (RN) packet to contend for identification. Collision happens when multiple tags select the same slot, which makes the RN packet undecodable and thus reduces the channel utilization. In this paper, we redesign the RN pattern to make the collided RNs decodable. By leveraging the collision slots, the system performance can be dramatically enhanced. This novel scheme is called DDC, which is able to directly decode the collisions without exact knowledge of collided RNs. In the DDC scheme, we modify the RN generator in RFID tag and add a collision decoding scheme for RFID reader. We implement DDC in GNU Radio and USRP2 based testbed to verify its feasibility. Both theoretical analysis and testbed experiment show that DDC achieves 40 percent tag read rate gain compared with traditional RFID protocol. [ABSTRACT FROM PUBLISHER]

Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e.g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations. [ABSTRACT FROM AUTHOR]

Intercontact time between moving vehicles is one of the key metrics in vehicular ad hoc networks (VANETs) and central to forwarding algorithms and the end-to-end delay. Due to prohibitive costs, little work has conducted experimental study on intercontact time in urban vehicular environments. In this paper, we carry out an extensive experiment involving thousands of operational taxies in Shanghai city. Studying the taxi trace data on the frequency and duration of transfer opportunities between taxies, we observe that the tail distribution of the intercontact time, that is, the time gap separating two contacts of the same pair of taxies, exhibits an exponential decay, over a large range of timescale. This observation is in sharp contrast to recent empirical data studies based on human mobility, in which the distribution of the intercontact time obeys a power law. By analyzing a simplified mobility model that captures the effect of hot areas in the city, we rigorously prove that common traffic influxes, where large volume of traffic converges, play a major role in generating the exponential tail of the intercontact time. Our results thus provide fundamental guidelines on design of new vehicular mobility models in urban scenarios, new data forwarding protocols and their performance analysis. [ABSTRACT FROM AUTHOR]