A radar observes the result of a space explosion. Due to the radar's low horizontal resolution, we get a 1D signal, x(t), representing different 2D slices. Based on these slices, we must distinguish between the bo...
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A radar observes the result of a space explosion. Due to the radar's low horizontal resolution, we get a 1D signal, x(t), representing different 2D slices. Based on these slices, we must distinguish between the body at the core of the explosion and the slowly out-moving fragments. We propose new algorithms for processing this 1D data. Since these algorithms are time-consuming, we also exploit the possibility of parallelizing these algorithms.
Network utility maximization problems provide an important approach to conduct network resource management such as power and rate allocation. In the existing literature, distributed implementations are typically achie...
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Network utility maximization problems provide an important approach to conduct network resource management such as power and rate allocation. In the existing literature, distributed implementations are typically achieved by the means of the so-called dual decomposition technique. However, the span of decomposition possibilities includes many other elements which thus far have not been fully exploited, such as the use of the primal decomposition technique, the versatile introduction of auxiliary variables, and the potential of multilevel decompositions. This paper presents in a systematic way how to apply these decomposition techniques to network utility maximization problems. The presentation is based on a general network optimization model that unifies existing works, and then is particularized to two concrete examples of recent interest: generalized water-filling algorithms and wireless cellular downlink power control. We can thus obtain a variety of distributed algorithms with different characteristics to suit the needs of specific applications. Both primal and dual decomposition techniques are considered at many different hierarchy levels, leading to a range of choices of hybrid, multi-level, primal/dual decomposition schemes. Each particular combination provides a different distributed algorithm for resource allocation. The choice of decomposition method and distributed algorithm for a particular problem depends on factors such as the amount of signalling required for proper coordination, asymmetry of computational load, and speed of convergence
The authors consider deadlock handling in distributed systems in which processes may reside at different sites interconnected by a communication network. In particular attention is given to distributed deadlock handli...
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The authors consider deadlock handling in distributed systems in which processes may reside at different sites interconnected by a communication network. In particular attention is given to distributed deadlock handling in which no site has the knowledge of the global state of process dependencies. A review of two distributed algorithms for deadlock handling is presented with emphasis on the proof technique. It is shown that the distributed algorithms for deadlock detection can be classified based on the technique used for dissemination of dependency information, namely, top-down or bottom-up. The algorithms when presented without details of implementation mechanisms permit proofs of correctness which are simpler.< >
LP relaxations of Maximum Weighted Independent Set (MWIS) problems have been widely studied. A key motivation for this prior work comes from the central role that MWIS plays in designing throughput-optimal algorithms ...
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ISBN:
(纸本)9781479933617
LP relaxations of Maximum Weighted Independent Set (MWIS) problems have been widely studied. A key motivation for this prior work comes from the central role that MWIS plays in designing throughput-optimal algorithms for wireless networks. However, to the best of our knowledge, the actual packet delay performance of these algorithms has not been studied in the context of wireless networks. In this paper, we first present an algorithm for solving the LP relaxation of MWIS which exhibits faster convergence to an optimal solution. Further, we show that one does not have to wait for infinite time for convergence to occur, but a simple rounding technique can be used to identify the ON/OFF states of the wireless links in finite time. As in prior work, such an approach only identifies the optimal MWIS states of some of the links in the network. Therefore, we present a scheme to combine this solution with Q-CSMA. Simulations indicate that the proposed scheme significantly improves the performance of Q-CSMA. Further, the proposed algorithm is shown to perform much better than previously suggested LP relaxation schemes due to its superior convergence properties.
When a vast number of camera sensors are randomly placed in a target field, how can we produce a sleep/activate schedule for camera sensors to maximize the lifetime of target coverage in the target field? This well-kn...
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When a vast number of camera sensors are randomly placed in a target field, how can we produce a sleep/activate schedule for camera sensors to maximize the lifetime of target coverage in the target field? This well-known problem is called Maximum Lifetime Coverage Problem (MLCP), which has been explored extensively in the literature. However, MLCP in full-view coverage camera sesnor networks are far more complicated since each target should be full-view covered by a group of camera sensors instead of a single sensor as in conventional scenarios. In this paper we address the full-view covered target problem, with the objective of maximizing the lifetime of a power constrained camera sensor network deployed for full-view coverage of targets with known location. We consider that a large number of camera sensors are placed randomly in close proximity of targets and each camera sensor sends the collected data to a base station. We define the camera sensor network lifetime as the time interval the targets are full-view covered by a camera sensor cover. Our contributions include: (1) an efficient data structure to represent a family of camera sensor cover, each of which full-view cover all targets with consideration of the lifetime of each camera sensor; (2) an energy efficient monitoring scheme where only the camera sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other camera sensors are in a low-energy sleep mode; (3) formulating the maximizing camera sensor network lifetime problem into a packing linear programming problem, where a modified Garg-Konemann Algorithm to find the near optimal solution is applied.
Dynamic Spectrum Management of Digital Subscriber Lines (DSL) has the potential to dramatically increase the capacity of the aging last-mile copper access network. This paper takes an important step toward fulfilling ...
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Dynamic Spectrum Management of Digital Subscriber Lines (DSL) has the potential to dramatically increase the capacity of the aging last-mile copper access network. This paper takes an important step toward fulfilling this potential through power spectrum balancing. We derive a novel algorithm called SCALE, that provides a significant performance improvement over the existing iterative water-filling (IWF) algorithm in multi-user DSL networks, doing so with comparable low complexity. The algorithm is easily distributed through measurement and limited message-passing with the use of a Spectrum Management Center. We outline how overhead can be managed, and show that in the limit of zero message-passing, performance reduces to IWF. Numerical convergence of SCALE was found to be extremely fast when applied to VDSL, with performance exceeding that of iterative water-filling in just a few iterations, and to over 90% of the final rate in under 5 iterations. Lastly, we return to the problem of iterative water-filling and derive a new algorithm named SCAWF that is shown to be a very simple way to waterfill, particularly suited to the multi-user context.
Doubly-stochastic matrices are usually required by consensus-based distributed algorithms. We propose a simple and efficient protocol and present some guidelines for implementing doubly-stochastic combination matrices...
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Doubly-stochastic matrices are usually required by consensus-based distributed algorithms. We propose a simple and efficient protocol and present some guidelines for implementing doubly-stochastic combination matrices even in noisy, asynchronous and changing topology scenarios. The proposed ideas are validated with the deployment of a wireless sensor network, in which nodes run a distributed algorithm for robust estimation in the presence of nodes with faulty sensors.
It is shown how fault-tolerant distributed algorithms can be formally verified using the Petri net based verification framework DAWN. A complete example study, the verification of a distributed self diagnosis algorith...
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It is shown how fault-tolerant distributed algorithms can be formally verified using the Petri net based verification framework DAWN. A complete example study, the verification of a distributed self diagnosis algorithm, is presented to demonstrate the benefits of the proposed approach.
In this paper we propose two algorithms for efficient data-centric storage in wireless sensor networks without the support of any location information system. These algorithms are intended to be applied in environment...
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In this paper we propose two algorithms for efficient data-centric storage in wireless sensor networks without the support of any location information system. These algorithms are intended to be applied in environments with large number of sensors where the scalability of the network has great issue. During the first algorithm, each sensor obtains a unique temporary address according to its current relative location in the network. The second algorithm is used to route data from one sensor to another, this routing algorithm only depends on the sensor's neighborhood, i.e. in order to implement the routing table each sensor needs only to exchange local information with its first hop neighbors. The forwarding process used in this algorithm resembles the one found in Pastry peer-to-peer protocol.
We present the object oriented design of a software system called NETMAN to experiment distributed algorithms on a large network of workstations. The design has been structured into three layers and a central monitori...
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ISBN:
(纸本)9780818685798
We present the object oriented design of a software system called NETMAN to experiment distributed algorithms on a large network of workstations. The design has been structured into three layers and a central monitoring site. We have implemented the system in Java. Two asynchronous communication primitives, SEND and RECEIVE, have been implemented using Java's remote method invocation mechanism. As an example, we executed a distributed mutual exclusion algorithm on a network of 60 workstations, and measured its performance under various scenarios.
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