Improved Shuffled Frog-Leaping Algorithm Based QoS Constrained Multicast Routing for Vanets

Prompt and reliable communication between vehicular nodes are essential as its limited coverage and dynamic mobility rate introduces frequent change of network topology. The key feature of vehicular communication that establishes direct connectivity or Road Side Unit-based data transfer among vehicular nodes is responsible for sharing emergency information during critical situations. Multicast routing data dissemination among vehicular nodes is considered to be the potential method of parallel data transfer as they facilitate the option of determining an optimal multicast tree from feasible number of multicast trees established between the source and destinations. This estimation of optimal multicast tree using meta-heuristic techniques is confirmed to improve the throughput and reliability of the network when QoS-based constraints are imposed during multicast routing. An Improved Shuffled Frog-Leaping Algorithm-Based QoS Constrained Multicast Routing (ISFLABMR) is proposed for estimating an optimal multicast tree that confirms effective multi-constrained applied multicast routing between vehicular nodes. ISFLABMR minimizes the cost of transmission to 22% by reducing the number of multicast clusters formed during multicasting through the utilization of local and global-based optimizations. The simulation results of ISFLABMR proveits predominant reduction rate of 24% and 21% in average packet latency and energy consumptions incurred under multicast routing.     

Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks

Due to inherent issue of energy limitation in sensor nodes, the energy conservation is the primary concern for large‐scale wireless sensor networks. Cluster‐based routing has been found to be an effective mechanism to reduce the energy consumption of sensor nodes. In clustered wireless sensor networks, the network is divided into a set of clusters; each cluster has a coordinator, called cluster head (CH). Each node of a cluster transmits its collected information to its CH that in turn aggregates the received information and sends it to the base station directly or via other CHs. In multihop communication, the CHs closer to the base station are burdened with high relay load; as a result, their energy depletes much faster as compared with other CHs. This problem is termed as the hot spot problem. In this paper, a distributed fuzzy logic‐based unequal clustering approach and routing algorithm (DFCR) is proposed to solve this problem. Based on the cluster design, a multihop routing algorithm is also proposed, which is both energy efficient and energy balancing. The simulation results reinforce the efficiency of the proposed DFCR algorithm over the state‐of‐the‐art algorithms, ie, energy‐aware fuzzy approach to unequal clustering, energy‐aware distributed clustering, and energy‐aware routing algorithm, in terms of different performance parameters like energy efficiency and network lifetime.     

A new delay‐constrained algorithm for multicast routing tree construction

New multimedia applications provide guaranteed end‐to‐end quality of service (QoS) and have stringent constraints on delay, delay‐jitter, bandwidth, cost, etc. The main task of QoS routing is to find a route in the network, with sufficient resources to satisfy the constraints. Most multicast routing algorithms are not fast enough for large‐scale networks and where the source node uses global cost information to construct a multicast tree. We propose a fast and simple heuristic algorithm (EPDT) for delay‐constrained routing problem for multicast tree construction. This algorithm uses a greedy strategy based on shortest‐path and minimal spanning trees. It combines the minimum cost and the minimum radius objectives by combining respectively optimal Prim's and Dijkstra's algorithms. It biases routes through destinations. Besides, it uses cost information only from neighbouring nodes as it proceeds, which makes it more practical, from an implementation point of view. Copyright © 2004 John Wiley & Sons, Ltd.     

Online Multicasting for Network Capacity Maximization in Energy-Constrained Ad Hoc Networks

In this paper, we present new algorithms for online multicast routing in ad hoc networks where nodes are energy-constrained. The objective is to maximize the total amount of multicast message data routed successfully over the network without any knowledge of future multicast request arrivals and generation rates. Specifically, we first propose an online algorithm for the problem based on an exponential function of energy utilization at each node. The competitive ratio of the proposed algorithm is analyzed if admission control of multicast requests is permitted. We then provide another online algorithm for the problem, which is based on minimizing transmission energy consumption for each multicast request and guaranteeing that the local network lifetime is no less than gamma times of the optimum, where gamma is constant with 0 < gammaleq 1. We finally conduct extensive experiments by simulations to analyze the performance of the proposed algorithms, in terms of network capacity, network lifetime, and transmission energy consumption for each multicast request. The experimental results clearly indicate that, for online multicast routing in ad hoc wireless networks, the network capacity is proportional to the network lifetime if the transmission energy consumption for each multicast request is at the same time minimized. This is in contrast to the implication by Kar et al. that the network lifetime is proportional to the network capacity when they considered the online unicast routing by devising an algorithm based on the exponential function of energy utilization at each node.     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

基于改进LEACH的多簇头分簇路由算法

为了降低无线传感器网络(WSN)的能耗,延长网络的生存周期,提出一种多簇头双工作模式的分簇路由算法.算法对低功耗自适应集簇分层(LEACH)协议作了以下改进:采用多簇头双工作模式来分担单簇头的负荷,以解决单簇头因能耗较大而过早消亡的问题;选举簇头时充分考虑节点位置和节点剩余能量,并应用粒子群优化(PSO)算法优化簇头的选举,以均衡网络内各节点的能耗;建立簇与簇之间的数据传输路由,以减少簇间通信的能耗.仿真结果表明,算法有效降低了网络的能耗,延长了网络的生存周期.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

Cross‐layer optimized routing in wireless sensor networks with duty cycle and energy harvesting

In this paper, we propose a cross‐layer optimized geographic node‐disjoint multipath routing algorithm, that is, two‐phase geographic greedy forwarding plus. To optimize the system as a whole, our algorithm is designed on the basis of multiple layers' interactions, taking into account the following. First is the physical layer, where sensor nodes are developed to scavenge the energy from environment, that is, node rechargeable operation (a kind of idle charging process to nodes). Each node can adjust its transmission power depending on its current energy level (the main object for nodes with energy harvesting is to avoid the routing hole when implementing the routing algorithm). Second is the sleep scheduling layer, where an energy‐balanced sleep scheduling scheme, that is, duty cycle (a kind of node sleep schedule that aims at putting the idle listening nodes in the network into sleep state such that the nodes will be awake only when they are needed), and energy‐consumption‐based connected k‐neighborhood is applied to allow sensor nodes to have enough time to recharge energy, which takes nodes' current energy level as the parameter to dynamically schedule nodes to be active or asleep. Third is the routing layer, in which a forwarding node chooses the next‐hop node based on 2‐hop neighbor information rather than 1‐hop. Performance of two‐phase geographic greedy forwarding plus algorithm is evaluated under three different forwarding policies, to meet different application requirements. Our extensive simulations show that by cross‐layer optimization, more shorter paths are found, resulting in shorter average path length, yet without causing much energy consumption. On top of these, a considerable increase of the network sleep rate is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Analysis of tree‐based multicast routing in wireless sensor networks with varying network metrics

Wireless ad hoc and sensor networks are emerging with advances in electronic device technology, wireless communications and mobile computing with flexible and adaptable features. Routing protocols act as an interface between the lower and higher layers of the network protocol stack. Depending on the size of target nodes, routing techniques are classified into unicast, multicast and broadcast protocols. In this article, we give analysis and performance evaluation of tree‐based multicast routing in wireless sensor networks with varying network metrics. Geographic multicast routing (GMR) and its variations are used extensively in sensor networks. Multicast routing protocols considered in the analytical model are GMR, distributed GMR, demand scalable GMR, hierarchical GMR, destination clustering GMR and sink‐initiated GMR. Simulations are given with comparative analysis based on varying network metrics such as multicast group size, number of sink nodes, average multicast latency, number of clusters, packet delivery ratio, energy cost ratio and link failure rate. Analytical results indicate that wireless sensor network multicast routing protocols operate on the node structure (such as hierarchical, clustered, distributed, dense and sparse networks) and application specific parameters. Simulations indicate that hierarchical GMR is used for generic multicast applications and that destination clustering GMR and demand scalable GMR are used for distributed multicast applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Increasing network lifetime by balancing node energy consumption in heterogeneous sensor networks

Sensor nodes are powered by battery and have severe energy constraints. The typical many‐to‐one traffic pattern causes uneven energy consumption among sensor nodes, that is, sensor nodes near the base station or a cluster head have much heavier traffic burden and run out of power much faster than other nodes. The uneven node energy dissipation dramatically reduces sensor network lifetime. In a previous work, we presented the chessboard clustering scheme to increase network lifetime by balancing node energy consumption. To achieve good performance and scalability, we propose to form a heterogeneous sensor network by deploying a few powerful high‐end sensors in addition to a large number of low‐end sensors. In this paper, we design an efficient routing protocol based on the chessboard clustering scheme, and we compute the minimum node density for satisfying a given lifetime constraint. Simulation experiments show that the chessboard clustering‐based routing protocol balances node energy consumption very well and dramatically increases network lifetime, and it performs much better than two other clustering‐based schemes. Copyright © 2006 John Wiley & Sons, Ltd.     

Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

The problems related to energy consumption and improvement of the network lifetime of WSN (wireless sensor network) have been considered. The base station (BS) location is the main concern in WSN. BSs are fixed, yet, they have the ability to move in some situations to collect the information from sensor nodes (SNs). Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the lifespan of the network. This paper proposes the assimilation of the fuzzy clustering approach and the Elephant Herding Optimization (EHO)‐Greedy algorithm for efficient routing in WSN. This work considers the separate sink nodes of a fixed sink and movable sink to decrease the utilization of energy. A fixed node is deployed randomly across the network, and the movable sink node moves to different locations across the network for collecting the data. Initially, the number of nodes is formed into the multiple clusters using the enhanced expectation maximization algorithm. After that, the cluster head (CH) selection done through a fuzzy approach by taking the account of three factors of residual energy, node centrality, and neighborhood overlap. A suitable collection of CH can extremely reduce the utilization of energy and also enhancing the lifespan. Finally, the routing protocol of the hybrid EHO‐Greedy algorithm is used for efficient data transmission. Simulation results display that the proposed technique is better to other existing approaches in regard to energy utilization and the system lifetime.     

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

The fundamental issues in mobile cognitive radio ad‐hoc networks are the selection of the optimal stable paths between nodes and proper assignment of the frequency channels/time slots (communication segments) to the links. In this paper, a joint load balanced stable routing and communication segment assignment algorithm is proposed that considers jointly the mobility prediction, mitigating the co‐channel interference and energy consumption. The novelty of the proposed algorithm lies in the increasing of the path stability, which benefits from the maximum link lifetime parameter and introduced weighting function to keep routes away from the PU's region. This avoids the negative impacts on the PUs' operations and decreases the conflict of the cognitive nodes. In the proposed algorithm, the concept of load balancing is considered that yields in the balancing energy consumption in the network, improving the network performance and distributing traffic loads on all available channels. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, average end‐to‐end delay, goodput, and the energy usage per packet under 6 scenarios. The results show that the performance of the proposed algorithm is significantly better than the recently proposed joint stable routing and channel assignment protocol.     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Energy Efficient Energy Hole Repelling (EEEHR) Algorithm for Delay Tolerant Wireless Sensor Network

Reducing energy consumption and increasing network lifetime are the major concerns in Wireless Sensor Network (WSN). Increase in network lifetime reduces the frequency of recharging and replacing batteries of the sensor node. The key factors influencing energy consumption are distance and number of bits transmitted inside the network. The problem of energy hole and hotspot inside the network make neighbouring nodes unusable even if the node is efficient for data transmission. Energy Efficient Energy Hole Repelling (EEEHR) routing algorithm is developed to solve the problem. Smaller clusters are formed near the sink and clusters of larger size are made with nodes far from the sink. This methodology promotes equal sharing of load repelling energy hole and hotspot issues. The opportunity of being a Cluster Head (CH) is given to a node with high residual energy, very low intra cluster distance in case of nodes far away from the sink and very low CH to sink distance for the nodes one hop from the sink. The proposed algorithm is compared with LEACH, LEACH-C and SEP routing protocol to prove its novel working. The proposed EEEHR routing algorithm provides improved lifetime, throughput and less packet drop. The proposed algorithm also reduces energy hole and hotspot problem in the network.     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Time‐aware and energy‐efficient opportunistic routing with residual energy collection in wireless sensor networks

In 1‐dimensional queue wireless sensor networks, how to balance end‐to‐end latency and energy consumption is a challenging problem. However, traditional best path routing and existing opportunistic routing protocols do not address them well because relay hop counts are usually much more, and the link appears more unreliable compared with general mesh topology. In this work, we formulate these 2 problems as a multiobjective optimization problem. Specifically, we first classify network packets into types of time tolerant and time critical and introduce a residual energy collection mechanism of neighboring nodes for forwarder set selection. We then propose a time‐aware and energy‐efficient opportunistic routing protocol (TE‐OR) to optimize energy consumption and to reduce latency for time‐critical packets. We evaluate TE‐OR by different parameters and compare it with existing protocols. The performance results show that TE‐OR achieves a trade‐off between energy consumption and time delay and balances energy consumption among nodes while guaranteeing the latency of time‐critical packets is minimized.     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

基于能量和密度的WSNs动态分区成簇路由算法

针对传统的层次型网络存在的分簇不合理和能耗不均衡等问题,提出了一种基于能量和密度的动态非均匀分区成簇路由算法。该算法先根据节点与基站之间的距离将网络合理地进行动态的区域划分,在区域内成簇,使靠近基站的簇规模小于距离基站较远的簇,减少靠近基站的簇首负担和能量消耗;通过综合考虑节点剩余能量和节点密度等因素来优化簇的非均匀划分和簇首的选择,簇首间采取基于数据聚合的多跳传输机制。仿真结果表明,与经典路由算法LEACH相比,该算法能有效均衡节点能耗,延长网络生命周期。     

Energy Efficient Cluster Based Routing Protocol for WSN Using Firefly Algorithm and Ant Colony Optimization

Maximizing network lifetime is the main goal of designing a wireless sensor network. Clustering and routing can effectively balance network energy consumption and prolong network lifetime. This paper presents a novel cluster-based routing protocol called EECRAIFA. In order to select the optimal cluster heads, Self-Organizing Map neural network is used to perform preliminary clustering on the network nodes, and then the relative reasonable level of the cluster, the cluster head energy, the average distance within the cluster and other factors are introduced into the firefly algorithm (FA) to optimize the network clustering. In addition, the concept of decision domain is introduced into the FA to further disperse cluster heads and form reasonable clusters. In the inter-cluster routing stage, the inter-cluster routing is established by an improved ant colony optimization (ACO). Considering factors such as the angle, distance and energy of the node, the heuristic function is improved to make the selection of the next hop more targeted. In addition, the coefficient of variation in statistics is introduced into the process of updating pheromones, and the path is optimized by combining energy and distance. In order to further improve the network throughput, a polling control mechanism based on busy/idle nodes is introduced during the intra-cluster communication phase. The simulation experiment results prove that under different application scenarios, EECRAIFA can effectively balance the network energy consumption, extend the network lifetime, and improve network throughput.

     

Power aware scalable multicast routing protocol for MANETs

Multicasting is an effective way to provide group communication. In mobile ad hoc networks (MANETs), multicasting can support a wide variety of applications that are characterized by a close degree of collaboration. Since MANETs exhibit severe resource constraints such as battery power, limited bandwidth, dynamic network topology and lack of centralized administration, multicasting in MANETs become complex. The existing multicast routing protocols concentrate more on quality of service parameters like end‐to‐end delay, jitter, bandwidth and power. They do not stress on the scalability factor of the multicast. In this paper, we address the problem of multicast scalability and propose an efficient scalable multicast routing protocol called ‘Power Aware Scalable Multicast Routing Protocol (PASMRP)’ for MANETs. PASMRP uses the concept of class of service with three priority levels and local re‐routing to provide scalability. The protocol also ensures fair utilization of the resources among the nodes through re‐routing and hence the lifetime of the network is increased. The protocol has been simulated and the results show that PASMRP has better scalability and enhanced lifetime than the existing multicast routing protocols. Copyright © 2005 John Wiley & Sons, Ltd.