Minimum Energy Broadcast Problem Research Articles

Flower Pollination Algorithm with Powell’s Method for the Minimum Energy Broadcast Problem in Wireless Sensor Network

Minimum energy broadcast (MEB) problem in wireless sensor network has attracted attentions of the many researchers due to the limited bandwidth of the network and battery life of the sensor nodes. The data in a wireless network are transmitted from the source node to all other nodes and seek broadcast scheme to transmit with minimum energy consumption. The main objective of MEB is to minimize the transmission energy consumption of the network and is considered as an NP-complete problem. This work proposes a new variant of Flower pollination algorithm based on Powell’s method (PFPA) to solve MEB problem in wireless sensor networks. The proposed algorithm is compared with other heuristic approaches and the performance of the algorithm is assessed using benchmark instances with 50 and 100 nodes. The effectiveness and merit of the proposed algorithm is demonstrated in terms of performance metrics.

An FPGA array for cellular genetic algorithms: Application to the minimum energy broadcast problem

The genetic algorithm is a general purpose optimization metaheuristic for solving complex optimization problems. Because the algorithm usually requires a large number of iterations to evolve a population of solutions to good final solutions, it normally exhibits long execution times, especially if running on low-performance conventional processors. In this work, we present a scalable computing array to parallelize and accelerate the execution of cellular GAs (cGAs). This is a variant of genetic algorithms which can conveniently exploit the coarse-grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and was implemented as an auxiliary processor of an embedded soft-core CPU (MicroBlaze). To facilitate the customization for different optimization problems, a high-level synthesis design flow is proposed where the problem-dependent operations are specified in C++ and synthesised to custom hardware, thus demanding of the programmer only minimal knowledge of low-level digital design for FPGAs. To demonstrate the efficiency of the array processor architecture and the effectiveness of the design methodology, the development of a hardware solver for the minimum energy broadcast problem in wireless ad hoc networks is employed as a use case. Implementation results for a Virtex-6 FPGA show significant speedups, especially when comparing to embedded processors used in current FPGA devices.

Clustering-Based Energy-Efficient Broadcast Tree in Wireless Networks

The characteristics of wireless networks present formidable challenges to the study of broadcasting problem. A crucial issue in wireless networks is the energy consumption, because of the nonlinear attenuation properties of radio signals. Another crucial issue is the trade-off between reaching more nodes in a single hop by using higher power versus reaching fewer nodes in that single hop by using lower power. Given a wireless network with a specified source node that broadcasts messages to all other nodes in the network, the minimum energy broadcast (MEB) problem is NP-hard. In this paper, we propose a hybrid approach CBEEB(clustering-based energy-efficient broadcast) for the MEB problem based on clustering. Theoretical analysis indicates the efficiency and effectiveness of CBEEB. Simulation results show that CBEEB has better performance compared with the existing heuristic approaches.

Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks (WANETs). The researches in WANETs have attracted significant attentions, and one of the most critical issues in WSNs is minimization of energy consumption. In WANETs the packets have to be transported from a given source node to all other nodes in the network, and the objective of the MEB problem is to minimize the total transmission power consumption. A hybrid algorithm based on particle swarm optimization (PSO) and local search is presented to solve the MEB problem. A power degree encoding is proposed to reflect the extent of transmission power level and is used to define the particle position in PSO. We also analyze a well-known local search mechanism, r-shrink, and propose an improved version, the intensified r-shrink. In order to solve the dynamic MEB problem with node removal/insertion, this paper provides an effective simple heuristic, Conditional Incremental Power (CIP), to reconstruct the broadcast network efficiently. The promising results indicate the potential of the proposed methods for practical use.

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

Memetic algorithm for minimum energy broadcast problem in wireless ad hoc networks

The problem of finding a broadcast tree with minimum power consumption has received much attention due to two reasons. They are (a) the limited bandwidth of wireless networks and (b) the nodes are battery operated. This work proposes heuristic memetic algorithm to find minimum energy broadcast tree in wireless ad hoc networks. The simulation results on numerous problem instances confirm that the proposed algorithm significantly outperforms several heuristic algorithms in terms of solution quality. The experimental evaluation of the memetic algorithm shows that it generally improves over other recently proposed algorithms. By solving well-known benchmark problem instances with 20 and 50 nodes, it also demonstrates the effectiveness of memetic algorithm in terms of computation time.

무선 센서 네트워크에서 최소 전력 브로드캐스트 문제를 위한 최적화 알고리즘

무선 네트워크에서 최소 에너지 브로드캐스트 문제는 네트워크에 배치된 모든 노드가 브로드캐스팅과정에서 데이터 전송에 사용되는 에너지를 최소화하는 문제이다. 본 논문은 무선 센서 네트워크에서 최소 에너지 브로드캐스트 문제를 효과적으로 해결할 수 있는 메타휴리스틱 기법인 타부서치 알고리즘을 제안한다. 보다 효과적인 해 검색을 위해 제안된 알고리즘은 새로운 이웃해 생성방식과 복구함수를 적용한다. 제안된 알고리즘의 성능평가는 배치된 모든 노드로의 브로드캐스팅 시 전송 에너지와 알고리즘 실행시간 관점에서 기존의 알고리즘과 비교를 하였으며, 실험 결과에서 제안된 알고리즘이 최소 에너지 브로드캐스트 문제에 효과적으로 적용됨을 보여준다. The minimum energy broadcast problem is for all deployed nodes to minimize a total transmission energy for performing a broadcast operation in wireless networks. In this paper, we propose a Tabu search algorithm to solve efficiently the minimum energy broadcast problem on the basis of meta-heuristic approach in wireless sensor networks. In order to make a search more efficient, we propose a novel neighborhood generating method and a repair function of the proposed algorithm. We compare the performance of the proposed algorithm with other existing algorithms through some experiments in terms of the total transmission energy of nodes and algorithm computation time. Experimental results show that the proposed algorithm is efficient for the minimum energy broadcast problem in wireless sensor networks.

Distributed ant colony optimization for minimum energy broadcasting in sensor networks with realistic antennas

One of the important tasks in wireless sensor networks is broadcasting, which arises when a sender node has to communicate information to all the other nodes of the network. In order to save energy, which is often a limited resource, broadcasting has to be done efficiently from an energy perspective. Energy efficiency can hereby be achieved by adjusting the transmission power levels of the sensor nodes’ antennas. This classical problem is known as the minimum energy broadcast (MEB) problem. In this work we deal with a generalization of this problem which is known as the minimum energy broadcast problem in sensor networks with realistic antennas (MEBRA). The difference to the classical MEB problem is to be found in a more realistic antenna model. In this work we propose a distributed ant colony optimization algorithm for solving the MEBRA problem. The experimental evaluation of the proposed algorithm shows that it generally improves over the centralized version of a classical heuristic. Moreover, depending on the exact antenna model used, the results of the distributed ant colony optimization algorithm are very close to the results of the centralized algorithm version.

Dual Decomposition for Computational Optimization of Minimum-Power Shared Broadcast Tree in Wireless Networks

We consider the problem of constructing a shared broadcast tree (SBT) in wireless networks, such that the total power required for supporting broadcast initiated by all source nodes is minimal. In the well-studied minimum-energy broadcast (MEB) problem, the optimal tree varies by source. In contrast, SBT is source-independent, thus substantially reducing the overhead for information storage and processing. The SBT problem also differs from the range assignment problem (RAP), because the power for message forwarding in SBT, although being source-independent, depends on from which tree neighbor the message is received. We approach SBT from a computational optimization standpoint, and present a dual decomposition method applied to an optimization model that embeds multiple directed trees into a shared tree. For the dual decomposition method, some of the constraints in the model are preferably formulated implicitly. The dual decomposition scheme is coupled with a fast local search algorithm. We report computational results demonstrating the effectiveness of the proposed approach. In average, the performance gap to global optimality is less than three percent.

An efficient approximation for minimum energy broadcast in multi-channel multi-hop wireless network with directional antennas

In this paper, We discuss the minimum energy broadcast problem (MEB) in multi-channel multi-hop wireless networks with directional antennas (MEB-MB). This problem is NP-hard since its special version, MEB in single-channel network with directional antennas (MEB-SB) is proved to be NP-hard. We design an efficient approximation for MEB-MB problem, analyze its approximation ratio, and evaluate its performance via numerical experiments.

Minimum energy broadcast on rectangular grid wireless networks

The minimum energy broadcast problem is to assign a transmission range to each node in an ad hoc wireless network to construct a spanning tree rooted at a given source node such that any non-root node resides within the transmission range of its parent. The objective is to minimize the total energy consumption, i.e., the sum of the δ th powers of a transmission range ( δ ≥ 1 ). In this paper, we consider the case that δ = 2 , and that nodes are located on a 2-dimensional rectangular grid. We prove that the minimum energy consumption for an n -node k × l -grid with n = k l and k ≤ l is at most n π + O ( n k 0.68 ) and at least n π + Ω ( n k ) − O ( k ) . Our bounds close the previously known gap of upper and lower bounds for square grids. Moreover, our lower bound is n 3 − O ( 1 ) for 3 ≤ k ≤ 18 , which matches a naive upper bound within a constant term for k ≡ 0 ( mod 3 ) .

Minimum energy broadcasting in wireless sensor networks: An ant colony optimization approach for a realistic antenna model

Abstract The classical minimum energy broadcast (MEB) problem in wireless adhoc networks, which is well-studied in the scientific literature, considers an antenna model that allows the adjustment of the transmission power to any desired real value from zero up to the maximum transmission power. However, when specifically considering sensor networks, a look at the currently available hardware shows that this antenna model is not very realistic. A first contribution of this work is therefore the re-formulation of the MEB problem for an antenna model that is realistic for sensor networks. In this antenna model transmission power levels are chosen from a finite set of possible ones. The second contribution concerns the adaptation of ant colony optimization, a current state-of-the-art algorithm for the classical MEB problem, to the more realistic problem version. The obtained results show that the advantage of ant colony optimization over classical heuristics even grows when the number of possible transmission power levels decreases.

A hybrid genetic algorithm for the minimum energy broadcast problem in wireless ad hoc networks

Given a wireless ad hoc network with a specified source node that has to broadcast messages to all other nodes in the network, the minimum energy broadcast (MEB) problem seeks a broadcast scheme for this network with minimum energy consumption. The MEB problem is NP-Hard. This paper describes a hybrid approach to the MEB problem combining a genetic algorithm with a local search heuristic. We have compared our hybrid approach against the best heuristic approaches known for this problem. Our approach outperformed all these approaches and emerged as the best.

Energy efficient all-to-all broadcast in all-wireless networks

All-to-all broadcast is a communication pattern in which every node initiates a broadcast. In this paper, we investigate the problem of building a unique cast tree of minimum total energy, which we call Minimum Unique Cast (MUC) tree, to be used for all-to-all broadcast. The MUC tree is unoriented and unrooted. We study three known heuristics for the minimum-energy broadcast problem: the Broadcast Incremental Power (BIP) algorithm, the Wireless Multicast Advantage-conforming Minimum Spanning Tree (WMA-conforming MST) algorithm, and the Iterative Maximum-Branch Minimization (IMBM) algorithm. Experimental results conducted on various types of networks are reported. We show that neither of these methods is best overall for building all-to-all broadcast trees.

Mixed integer formulations for the probabilistic minimum energy broadcast problem in wireless networks

In this paper we study a new variant of the minimum energy broadcast (MEB) problem, namely the probabilistic MEB (PMEB). The objective of the classic MEB problem is to assign transmission powers to the nodes of a wireless network is such a way that the total energy dissipated on the network is minimized, while a connected broadcasting structure is guaranteed by the assigned transmission powers. In the new variant of the problem treated in this paper, node failure is taken into account, aiming at providing solutions with a chosen reliability level for the broadcasting structure. Three mixed integer linear programming formulations for the new problem are presented, together with efficient formulation-dependent methods for their solution. Computational results are proposed and discussed. One method emerges as the most promising one under realistic settings. It is able to handle problems with up to fifty nodes.

Minimum-Energy Broadcast and disk cover in grid wireless networks

The Minimum-Energy Broadcast problem is to assign a transmission range to every station of an ad hoc wireless networks so that (i) a given source station is allowed to perform broadcast operations and (ii) the overall energy consumption of the range assignment is minimized. We prove a nearly tight asymptotical bound on the optimal cost for the Minimum-Energy Broadcast problem on square grids. We also derive near-tight bounds for the Bounded-Hop version of this problem. Our results imply that the best-known heuristic, the MST-based one, for the Minimum-Energy Broadcast problem is far to achieve optimal solutions (even) on very regular, well-spread instances: its worst-case approximation ratio is about π and it yields Ω ( n ) hops, where n is the number of stations. As a by product, we get nearly tight bounds for the Minimum-Disk Cover problem and for its restriction in which the allowed disks must have non-constant radius. Finally, we emphasize that our upper bounds are obtained via polynomial time constructions.

Minimum-Energy Broadcasting in Multi-hop Wireless Networks Using a Single Broadcast Tree

In this paper we address the minimum-energy broadcast problem in multi-hop wireless networks, so that all broadcast requests initiated by different source nodes take place on the same broadcast tree. Our approach differs from the most commonly used one where the determination of the broadcast tree depends on the source node, thus resulting in different tree construction processes for different source nodes. Using a single broadcast tree simplifies considerably the tree maintenance problem and allows scaling to larger networks. We first show that, using the same broadcast tree, the total power consumed for broadcasting from a given source node is at most twice the total power consumed for broadcasting from any other source node. We next develop a polynomial-time approximation algorithm for the construction of a single broadcast tree. The performance analysis of the algorithm indicates that the total power consumed for broadcasting from any source node is within 2H(n-1) from the optimal, where n is the number of nodes in the network and H(n) is the harmonic function. This approximation ratio is close to the best achievable bound in polynomial time. We also provide a useful relation between the minimum-energy broadcast problem and the minimum spanning tree, which shows that a minimum spanning tree may be a good candidate in sparsely connected networks. The performance of our algorithm is also evaluated numerically with simulations.

A combination of wireless multicast advantage and hitch-hiking

In the minimum energy broadcast problem, each node adjusts its transmission power to minimize the total energy consumption while still delivering data to all the nodes in a network. The minimum energy broadcast problem is proved to be NP-complete. The Wireless Multicast Advantage (WMA) is that a single transmission can be received by all the nodes that are within the transmission range of a transmitting node. The Hitch-hiking model introduced recently takes advantage of the physical layer to combine partial signals containing the same data in order to decode a complete message. In this letter, we take advantage of both WMA and Hitch-hiking to design an energy-efficient broadcast tree algorithm with Hitch-hiking (BHH). The approximation ratio of BHH is within a factor of O(logn) where n, is the number of nodes in the network. The simulation results show that BHH reduces the total energy of the broadcast tree greatly.

Cooperative Multihop Broadcast for Wireless Networks

We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart.