Joint multi-radio multi-channel assignment, scheduling, and routing in wireless mesh networks

The IEEE 802.11 DCF and EDCA mechanisms based on CSMA/CA are the most widely used random channel access mechanisms in wireless mesh networks (WMNs), but unfortunately these cannot effectively eliminate hidden terminal and exposed terminal problems in multi-hop scenarios. In this paper, we propose a set of efficient multi-radio multi-channel (MRMC) assignment, scheduling and routing protocols based on Latin squares for WMNs with MRMC communication capabilities, called “M4”, i.e., the Multiple access scheduling in Multi-radio Multi-channel Mesh networking. M4 uses nodal interference information to form cliques for inter-cluster and intra-cluster inWMNs, and then applies Latin squares to map the clique-based clustering structure to radios and channels for communication purposes. Then, M4 again applies Latin squares to schedule the channel access among nodes within each cluster in a collision-free manner. From a systematic view, we also design the corresponding MRMC routing to support M4 communication. Extensive simulation results show that M4 achieves much better performance than IEEE 802.11 standards and other channel access control protocols.     

Coexistence of 2.4 GHz sensor networks in home environment

The IEEE 802.15.4 is one of the low-layer communication standards for personal area networks(PANs) and wireless sensor networks(WSNs),which may be interfered by other wireless devices in the industrial,scientific and medical(ISM) frequency bands,especially in home environment,such as devices of IEEE 802.11b,Bluetooth,cordless telephone,and microwave oven radiation.This article examines the mutual interference effects of 2.4 GHz devices widely deployed at home,via both theoretical analysis and real-life expe...     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

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.     

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.     

Coexistence Performance of IEEE 802.15.4 Wireless Sensor Networks Under IEEE 802.11b/g Interference

IEEE 802.15.4 Wireless Sensor Networks (WSNs) and IEEE 802.11b/g Wireless Local Area Networks (WLANs) are often collocated, causing a coexistence issue since these networks share the same 2.4GHz Industrial, Scientific, and Medical band. In our previous work, we built a coexistence model of IEEE 802.15.4 WSNs and IEEE 802.11b/g WLANs. By identifying three distinct coexistence regions, the model explained the coexistence behavior of IEEE 802.15.4 WSNs and IEEE 802.11b/g WLANs, and the model was experimentally validated. In this paper, we improve the model by introducing two important implementation factors: the transceiver’s Rx-to-Tx turnaround time and the Clear Channel Assessment partial detection effect. The enhanced model significantly improves the accuracy on explaining and predicting the coexistence performance of IEEE 802.15.4 WSNs in the real-life environment. Furthermore, under the guidance of the model, the coexistence performance of IEEE 802.15.4 WSNs is extensively investigated in various coexistence scenarios by analysis, simulation and experiments, respectively. The simulation and experimental results agree with our analysis. The coexistence model is believed to be helpful in resolving the coexistence issue.     

Throughput analysis of IEEE 802.15.4 network under IEEE 802.11 network interference

This paper evaluates throughput of IEEE 802.15.4 network under the interference of a saturated IEEE 802.11 network using an analytic method. Packet losses due to both collisions among IEEE 802.15.4 and mutual interference between IEEE 802.15.4 and 802.11 are considered for throughput analysis. To include the interference from IEEE 802.11, we modified the state transition probabilities of IEEE 802.15.4 two-state Markov process model. Simulation results closely match the theoretical expressions confirming the effectiveness of the proposed model.     

一种负载均衡且能量高效的水下传感网络分簇协议

针对水下无线传感网络能量效率低、生命周期短的问题,提出了一种负载均衡且能量高效的水下分簇（load balanced and energy efficient underwater clustering,LBEEUC）协议。该算法在分簇过程中首先根据节点的经验负载来确定节点所在区域簇头的比例,使经验负载大的区域分布较多的簇头,分担数据转发的任务,均衡网络的能耗;其次在节点入簇时,在簇内设置中继节点,用于均衡远离簇头节点的传输能耗,并提前进行数据融合,减少数据冗余;最后在建立簇间路由时,利用Q 学习算法根据路径消耗的总能量最小的原则选择最优传输路径。仿真结果表明,本算法有效地均衡了网络的能耗,提高了能量利用效率,进而提高了网络的生存时间。     

Priority-based IEEE 802.15.4 CSMA/CA mechanism for WSNs

The IEEE 802.15.4 standard is widely used in wireless sensor networks (WSNs). In this paper, we propose a priority-based IEEE 802.15.4 carrier sense multiple access with collision avoidance (CSMA/CA) mechanism for WSNs. Considering traffic load and traffic type of sensor nodes, we classify sensor nodes into three types. In our mechanism, different contention parameters are set for nodes with different priority levels, in order that nodes with high priority achieve high probability to access the channel. By modeling the proposed mechanism using a Markov chain, we analyze and compute the successful transmission probability, throughput and energy consumption for nodes with different priority levels. Finally, our numerical results demonstrate that our mechanism performs well for WSNs.     

Multi-objective-derived energy efficient routing in wireless sensor networks using hybrid African vultures-cuckoo search optimization

Wireless Sensor Network (WSN) plays an essential role in consumer electronics, remote monitoring, an electromagnetic signal, and so forth. The functional capacity of WSN gets enhanced everyday with different technologies. The rapid development of wireless communication, as well as digital electronics, provides automatic sensor networks with low cost and power in various functions, but the challenge faced in WSN is to forward a huge amount of data between the nodes, which is a highly complex task to provide superior delay and energy loss. To overcome these issues, the development of a routing protocol is used for the optimal selection of multipath to perform efficient routing in WSN. This paper developed an energy-efficient routing in WSNs utilizing the hybrid meta-heuristic algorithm with the help of Hybrid African Vultures-Cuckoo Search Optimization (HAV-CSO). Here, the designed method is utilized for choosing the optimal cluster heads for progressing the routing. The developed HAV-CSO method is used to enhance the network lifetime in WSN. Hence, the hybrid algorithm also helps select the cluster heads by solving the multi-objective function in terms of distance, intra-cluster distance, delay, inter-cluster distance, throughput, path loss, energy, transmission load, temperature, and fault tolerance. The developed model achieved 7.8% higher than C-SSA, 25.45% better than BSO-MTLBO, 23.21% enhanced than AVOA, and 1.29% improved than CSO. The performance of the suggested model is validated, and the efficacy of the developed work is proved over other existing works.     

Clustering and power management for virtual MIMO communications in wireless sensor networks

Multi-input multi-output (MIMO) is a well-established technique for increasing the link throughput, extending the transmission range, and/or reducing energy consumption. In the context of wireless sensor networks (WSNs), even if each node is equipped with a single antenna, it is possible to group several nodes to form a virtual antenna array, which can act as the transmitting or receiving end of a virtual MIMO (VMIMO) link. In this paper, we propose energy-efficient clustering and power management schemes for virtual MIMO operation in a multi-hop WSN. Our schemes are integrated into a comprehensive protocol, called cooperative MIMO (CMIMO), which involves clustering the WSN into several clusters, each managed by up to two cluster heads (CHs); a master CH (MCH) and a slave CH (SCH). The MCH and SCH collect data from their cluster members during the intra-cluster communications phase and communicate these data to neighboring MCHs/SCHs via an inter-cluster VMIMO link. CMIMO achieves energy efficiency by proper selection of the MCHs and SCHs, adaptation of the antenna elements and powers in the inter-cluster communications phase, and using a cross-layer MIMO-aware route selection algorithm for multi-hop operation. We formally establish the conditions on the transmission powers of CHs and non-CHs that ensure the connectivity of the inter-cluster topology. Simulations are used to study the performance of CMIMO. The simulation results indicate that our proposed protocol achieves significant reduction in energy consumption and longer network life time, compared with non-adaptive clustered WSNs.     

MST-based clustering topology control algorithm for wireless sensor networks

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes’ transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy &; Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs’ transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs’ transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node’s degree, average node’s power radius and network lifetime, respectively.     

A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic

Recently, Internet is moving quickly toward the interaction of objects, computing devices, sensors, and which are usually indicated as the Internet of things (IoT). The main monitoring infrastructure of IoT systems main monitoring infrastructure of IoT systems is wireless sensor networks. A wireless sensor network is composed of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. The sensor nodes send the data to a sink or a base station by using wireless transmission techniques However, sensor network systems require suitable routing structure to optimizing the lifetime. For providing reasonable energy consumption and optimizing the lifetime of WSNs, novel, efficient and economical schemes should be developed. In this paper, for enhancing network lifetime, a novel energy-efficient mechanism is proposed based on fuzzy logic and reinforcement learning. The fuzzy logic system and reinforcement learning is based on the remained energies of the nodes on the routes, the available bandwidth and the distance to the sink. This study also compares the performance of the proposed method with the fuzzy logic method and IEEE 802.15.4 protocol. The simulations of the proposed method which were carried out by OPNET (Optimum Network performance) indicated that the proposed method performed better than other protocols such as fuzzy logic and IEEE802.15.4 in terms of power consumption and network lifetime.

     

A novel method for mitigating the effects of dynamic coexistence on the operation of IEEE 802.15.4‐based mobile WSNs

Wireless networks dynamically coexist when their transmission ranges overlap as a result of mobility. Mobile wireless sensor networks (WSNs) may suffer from significant degradation of performance due to the interference caused by dynamic coexistence, which is particularly critical for health monitoring WSNs. In this paper, we propose a novel method to detect and mitigate the harmful effects of dynamic coexistence on the operation of IEEE 802.15.4‐based mobile health monitoring WSNs. IEEE 802.15.4 uses the guaranteed time slots (GTS) mechanism to eliminate contention; however, successful transmissions cannot be guaranteed for coexisting WSNs. We show that using limited clear channel assessments at the beginning of the GTS enables the mobile WSNs to avoid collisions with minimum overhead. This method can also be used in combination with the previously proposed mechanisms for coexistence management. We analytically investigate the effects of using this method on the performance of the dynamically coexisting WSNs. We use OPNET simulation to investigate the coexistence of health monitoring WSNs and also to validate the proposed method. Our results indicate that using the proposed mechanism, 2–10 coexisting mobile WSNs with relatively high transmission rates (20–30% of maximum throughput) can achieve 20–90% higher rates of successful transmissions, with less than 10% increase in power consumption. Copyright © 2014 John Wiley & Sons, Ltd.     

A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks

Clustering has been proven to be one of the most efficient techniques for saving energy of wireless sensor networks (WSNs). However, in a hierarchical cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving and aggregating the data from their member sensor nodes and transmitting the aggregated data to the base station. Therefore, the proper selection of CHs plays vital role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient cluster head selection algorithm which is based on particle swarm optimization (PSO) called PSO-ECHS. The algorithm is developed with an efficient scheme of particle encoding and fitness function. For the energy efficiency of the proposed PSO approach, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes. We also present cluster formation in which non-cluster head sensor nodes join their CHs based on derived weight function. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The results are compared with some existing algorithms to demonstrate the superiority of the proposed algorithm.     

Energy Efficient Four Level Cooperative Opportunistic Communication for Wireless Personal Area Networks (WPAN)

For wireless sensor networks (WSNs), energy is a scarce resource. Due to limited battery resources, the energy consumption is the critical issue for the transmission as well as reception of the signals in the wireless communication. WSNs are infrastructure-less shared network demanding more energy consumption due to collaborative transmissions. This paper proposes a new cooperative opportunistic four level model for IEEE 802.15.4 wireless personal area network. The average per node energy consumption is observed merely about 0.17 mJ for the cooperative wireless communication which proves the proposed mechanism to be energy efficient. This paper further proposes four levels of cooperative data transmission from source to destination to improve network coverage with energy efficiency.     

uSensing:一种支撑智能手机接入无线传感器网络的跨平台系统

This paper presents a universal platform “uSensing”to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs). Since phones have different CPU processers and operating systems, it is a challenge to merge these heterogeneities and develop such a universal platform. In this paper, we design both hardware and software to support the “universal”feature of uSensing: 1) “uSD”card: an IEEE 802.15.4 physical communication card with SD interface; 2) “uSink-Ware”: a WSNs middleware running on smartphones. Integrated with uSD card and uSinkWare, phones become mobile data sinks to access into WSNs and parse messages from sensor nodes. We demonstrate the proposed uSensing platform in a commercial smartphone to connect with our WSNs testbed, and validate that the smartphone has the same WSNs functions as commercial fixed sink. Additionally, we evaluate the performance of uSensing platform through measuring phone's CPU load and power consumption, and analyze the performance of these metrics theoretically. The results suggest that the phone-based mobile sink has enough capability to serve as a mobile sink of WSNs and can work up to twenty hours due to low power consumption.     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.     

An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks

In wireless sensor networks (WSNs), clustering can significantly reduce energy dissipation of nodes, and also increase communication load of cluster heads. When multi-hop communication model is adopted in clustering, “energy hole” problem may occur due to unbalanced energy consumption among cluster heads. Recently, many multi-hop clustering protocols have been proposed to solve this problem. And the main way is using unequal clustering to control the size of clusters. However, many of these protocols are about homogeneous networks and few are about heterogeneous networks. In this paper, we present an unequal cluster-based routing scheme for WSNs with multi-level energy heterogeneity called UCR-H. The sensor field is partitioned into a number of equal-size rectangular units. We first calculate the number of clusters in each unit by balancing energy consumption among the cluster heads in different units. And then we find the optimal number of units by minimizing the total energy consumption of inter-cluster forwarding. Finally, the size of clusters in each unit is elaborately designed based on node’s energy level and the number of clusters in this unit. And a threshold is also designed to avoid excessive punishment to the nodes with higher energy level. Simulation results show that our scheme effectively mitigates the “energy hole” problem and achieves an obvious improvement on the network lifetime.     

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks(WSNs).In order to minimize energy consumption and balance energy dissipation throughout the whole network,a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper.This scheme studies energy efficiency in systematic view.For three main steps,namely nodes clustering,data aggregation and cooperative transmission,corresponding measures are put forward to save energy.These measures are well designed and tightly coupled to achieve optimal performance.A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes.Based on clusters built,data aggregation,with the adoption of dynamic data compression,is performed by cluster heads to get better use of data correlation.Cooperative multiple input multiple output(CMIMO) with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node.System model of this scheme is also given in this paper.And simulation results show that,compared with other traditional schemes,the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency,which leads to longer network lifetime span.By adopting orthogonal space time block code(STBC),the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded,which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.