In this paper we study the gossiping problem (all-to-all communication) in radio networks where all nodes are aware of the network topology. We start our presentation with a deterministic gossiping algorithm that work...
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In this paper we study the gossiping problem (all-to-all communication) in radio networks where all nodes are aware of the network topology. We start our presentation with a deterministic gossiping algorithm that works in at most n units of time in any radio network of size n. This algorithm is optimal in the worst case scenario since there exist radio network topologies, such as lines, stars and complete graphs in which radio gossiping cannot be completed in less than n communication rounds. Furthermore, we show that there does not exist any radio network topology in which the gossiping task can be solved in less than [log(n - 1)] +2 rounds. We also show that this lower bound can be matched from above for a fraction of all possible integer values of n, and for all other values of n we propose a solution which accomplishes gossiping in [log(n - 1)] + 2 rounds. Then we show an almost optimal radio gossiping algorithm in trees, which misses the optimal time complexity by a single round. Finally, we study asymptotically optimal O(D)-time gossiping (where D is the diameter of the network) in graphs with the maximum degree Delta = O(D1-1/(i+1)/log(i) n), for any integer constant i >= 0 and D large enough. (c) 2007 Elsevier B.V. All rights reserved.
The significant growth in the number of WiFi-enabled devices as well as the increase in the traffic conveyed through wireless local area networks (WLANs) necessitate the adoption of new network control mechanisms. Spe...
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The significant growth in the number of WiFi-enabled devices as well as the increase in the traffic conveyed through wireless local area networks (WLANs) necessitate the adoption of new network control mechanisms. Specifically, dense deployment of access points, client mobility, and emerging QoS demands bring about challenges that cannot be effectively addressed by distributed mechanisms. Recent studies show that software-defined WLANs (SDWLANs) simplify network control, improve QoS provisioning, and lower the deployment cost of new network control mechanisms. In this paper, we present an overview of SDWLAN architectures and provide a qualitative comparison in terms of features such as programmability and virtualization. In addition, we classify and investigate the two important classes of centralized network control mechanisms: 1) association control and 2) channel assignment. We study the basic ideas employed by these mechanisms, and in particular, we focus on the metrics utilized and the problem formulation techniques proposed. We present a comparison of these mechanisms and identify open research problems.
In recent years, wireless sensor network (WSN) is one of the rapidly growing area in various domains such as disaster relief operation, military applications, health applications, etc. In WSN, to eliminate the redunda...
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In recent years, wireless sensor network (WSN) is one of the rapidly growing area in various domains such as disaster relief operation, military applications, health applications, etc. In WSN, to eliminate the redundant information from the gathered data, data aggregation is a prime approach by which we can considerably reduce the energy consumption of each node. This reduction supports the achievement of the higher lifetime of WSN. In this paper, we have endeavored to introduce a review of various existing data aggregation algorithms in the literature. We have also tried to summarize all these existing data aggregation algorithms on the basis of different performance metrics such as energy consumption, network lifetime, delay, energy cost, etc. Finally, this paper supports the reader an idea to select the data aggregation algorithm for the desired application. (C) 2020 Elsevier B.V. All rights reserved.
In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displac...
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In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displacement of camera-sensor nodes in the bounded field of interest (FoI), where the network coverage in terms of every point in the FoI is important. The proposed work is first of its kind to study the problem of maximizing coverage of randomly deployed mobile WCSNs which exploits their mobility. We propose an algorithm uncovered region exploration algorithm (UREA-CS) that can be executed in centralized and distributed modes. Further, the work is extended for two special scenarios: 1) to suit autonomous combing operations after initial random WCSN deployments and 2) to improve the network coverage with occlusions in the FoI. The extensive simulation results show that the performance of UREA-CS is consistent, robust, and versatile to achieve maximum coverage, both in centralized and distributed modes. The centralized and distributed modes are further analyzed with respect to the computational and communicational overheads.
This paper proposes energy-efficient coordinated beamforming strategies for multicell multiuser multiple-input single-output system. We consider a practical power consumption model, where part of the consumed power de...
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This paper proposes energy-efficient coordinated beamforming strategies for multicell multiuser multiple-input single-output system. We consider a practical power consumption model, where part of the consumed power depends on the base station or user specific data rates due to coding, decoding, and backhaul. This is different from the existing approaches where the base station power consumption has been assumed to be a convex or linear function of the transmit powers. Two optimization criteria are considered, namely network energy efficiency maximization and weighted sum energy efficiencymaximization. We develop successive convex approximation-based algorithms to tackle these difficult nonconvex problems. We further propose decentralized implementations for the considered problems, in which base stations perform parallel and distributed computation based on local channel state information and limited backhaul information exchange. The decentralized approaches admit closed-form solutions and can be implemented without invoking a generic external convex solver. We also show an example of the pilot contamination effect on the energy efficiency using a heuristic pilot allocation strategy. The numerical results are provided to demonstrate that the rate dependent power consumption has a large impact on the system energy efficiency, and, thus, has to be taken into account when devising energy-efficient transmission strategies. The significant gains of the proposed algorithms over the conventional low-complexity beamforming algorithms are also illustrated.
Association and sequential rules have received much attention in both academia and in practice for quite some time. A number of algorithms have been proposed to improve the efficiency of mining decision rules. However...
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ISBN:
(纸本)9781509049172
Association and sequential rules have received much attention in both academia and in practice for quite some time. A number of algorithms have been proposed to improve the efficiency of mining decision rules. However, these centralized algorithms have been criticized for their inapplicability to distributed environments. Although many sophisticated distributed algorithms for mining association and sequential rules have been proposed in recent years, they are not supported by most popular software programs;this decreases the possible applications of decision rules. In addition, past decision rules have only focused on the rules for which items exist. Some important decision rules might be lost if suitable items do not exist. In this paper, we propose an integrated framework to combine centralized algorithms, such as the Frequent Pattern Growth (FP-Growth), Sequential Pattern Discovery using Equivalence classes ( SPADE), and rough set algorithms, to mine decision rules in a distributed environment. In addition, our method finds some significant rules that other algorithms cannot. The experiments also demonstrate that the proposed method is well suited to finding association and sequential rules in a distributed environment.
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