Path scheduling for multiple mobile actors in wireless sensor network

In wireless sensor network (WSN), energy is the main constraint. In this work we have addressed this issue for single as well as multiple mobile sensor actor network. In this work, we have proposed Rendezvous Point Selection Scheme (RPSS) in which Rendezvous Nodes are selected by set covering problem approach and from that, Rendezvous Points are selected in a way to reduce the tour length. The mobile actors tour is scheduled to pass through those Rendezvous Points as per Travelling Salesman Problem (TSP). We have also proposed novel rendezvous node rotation scheme for fair utilisation of all the nodes. We have compared RPSS with Stationery Actor scheme as well as RD-VT, RD-VT-SMT and WRP-SMT for performance metrics like energy consumption, network lifetime, route length and found the better outcome in all the cases for single actor. We have also applied RPSS for multiple mobile actor case like Multi-Actor Single Depot (MASD) termination and Multi-Actor Multiple Depot (MAMD) termination and observed by extensive simulation that MAMD saves the network energy in optimised way and enhance network lifetime compared to all other schemes.     

SGDD: self‐managed grid‐based data dissemination protocol for mobile sink in wireless sensor network

The reduction of energy consumption in order to increase network lifetime is one of the most major challenges in the design of wireless sensor networks. During data dissemination, the sensors that are located in the sink's neighborhood are responsible to relay data to the other nodes; hence, their energy is exhausted expeditiously. Therefore, the idea of utilizing mobile sinks can be so advantageous to decrease energy consumption during data dissemination process. In this paper, we propose self‐managed grid‐based data disseminating protocol for mobile sink in wireless sensor networks by using the idea of constructing a virtual grid. In self‐managed grid‐based data disseminating protocol, sink and nodes map their geographical position to a virtual location. In order to increase the performance, we have employed a cell head for each grid cell. Cell heads are selected based on two parameters, centralization and residual energy. Our data dissemination protocol is simple and has low overhead to construct and maintain. Also, we have presented a new method for sink location update, which leads to the least cost in data transfer. Simulation results illustrate that by utilizing hierarchical functionality and determining an optimal size for grid cells, energy consumption is decreased, which leads to increasing network lifetime. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy‐conserving data gathering by mobile mules in a spatially separated wireless sensor network

This paper considers a spatially separated wireless sensor network, which consists of a number of isolated subnetworks that could be far away from each other in distance. We address the issue of using mobile mules to collect data from these sensor nodes. In such an environment, both data‐collection latency and network lifetime are critical issues. We model this problem as a bi‐objective problem, called energy‐constrained mule traveling salesman problem (EM‐TSP), which aims at minimizing the traversal paths of mobile mules such that at least one node in each subnetwork is visited by a mule and the maximum energy consumption among all sensor nodes does not exceed a pre‐defined threshold. Interestingly, the traversal problem turns out to be a generalization of the classical traveling salesman problem (TSP), an NP‐complete problem. With some geometrical properties of the network, we propose some efficient heuristics for EM‐TSP. We then extend our heuristics to multiple mobile mules. Extensive simulation results have been conducted, which show that our proposed solutions usually give much better solutions than most TSP‐like approximations. Copyright © 2011 John Wiley & Sons, Ltd.     

A mobile sink path planning for wireless sensor networks based on priority‐ordered dependent nonparametric trees

The professional design of the routing protocols with mobile sink(s) in wireless sensor networks (WSNs) is important for many purposes such as maximizing energy efficiency, increasing network life, and evenly distributing load balance across the network. Moreover, mobile sinks ought to first collect data from nodes which have very important and dense data so that packet collision and loss can be prevented at an advanced level. For these purposes, the present paper proposes a new mobile path planning protocol by introducing priority‐ordered dependent nonparametric trees (PoDNTs) for WSNs. Unlike traditional clustered or swarm intelligence topology‐based routing methods, a topology which has hierarchical and dependent infinite tree structure provides a robust link connection between nodes, making it easier to reselect ancestor nodes (ANs). The proposed priority‐ordered infinite trees are sampled in the specific time frames by introducing new equations and hierarchically associated with their child nodes starting from the root node. Hence, the nodes with the highest priority and energy that belong to the constructed tree family are selected as ANs with an opportunistic approach. A mobile sink simply visits these ANs to acquire data from all nodes in the network and return to where it started. As a result, the route traveled is assigned as the mobile path for the current round. We have performed comprehensive performance analysis to illustrate the effectiveness of the present study using NS‐2 simulation environment. The present routing protocol has achieved better results than the other algorithms over various performance metrics.     

GCRP: Grid-cycle routing protocol for wireless sensor network with mobile sink

Energy conservation is a critical issue in resource constraint wireless sensor networks. Employing mobile sink to deliver the sensed data becomes pervasive approach to conserve sensors’ limited energy. However, mobile sink makes data delivery a hard nut to crack since nodes need to know its latest location. Providing sink’s latest location by traditional flooding, erode the energy conservation goal. In this paper, we propose a Grid-Cycle Routing Protocol (GCRP) with the aim of minimizing the overhead of updating the mobile sink’s latest location. In GCRP, sensor field is partitioned into grid of cells and for each cell a grid cell head (GCH) is elected. Cycles of four GCHs is formed. Cycle(s) involving border GCHs is called exterior cycle and said to belong to a region. Another cycle involving non-boundary GCHs is called interior cycle, connecting GCHs of different regions. When sink stays at one location, it updates the nearest GCH, which in turn updates the other GCHs through exterior and interior cycle. Moreover, we propose a set of sharing rules that govern GCHs when and with who share sink’s latest location information. The performance of GCRP is evaluated at different number of nodes and compared with existing work using NS-2.31.     

A novel approach for designing delay efficient path for mobile sink in wireless sensor networks

In the recent years, the use of mobile sink has drawn enormous attention for data collection in wireless sensor networks (WSNs). Mobile sink is well known for solving hotspot or sinkhole problem. However, the design of an efficient path for mobile sink has tremendous impact on network lifetime and coverage in data collection process of WSNs. This is particularly an important issue for many critical applications of WSNs where data collection requires to be carried out in delay bound manner. In this paper, we propose a novel scheme for delay efficient trajectory design of a mobile sink in a cluster based WSN so that it can be used for critical applications without compromising the complete coverage of the target area. Given a set of gateways (cluster heads), our scheme determines a set of rendezvous points for designing path of the mobile sink for critical applications. The scheme is based on the Voronoi diagram. We also propose an efficient method for recovery of the orphan sensor nodes generated due to the failure of one or more cluster heads during data collection. We perform extensive simulations over the proposed algorithm and compare its results with existing algorithms to demonstrate the efficiency of the proposed algorithm in terms of network lifetime, path length, average waiting time, fault tolerance and adaptability etc. For the fault tolerance, we simulate the schemes using Weibull distribution and analyze their performances.     

Energy efficient path selection for mobile sink and data gathering in wireless sensor networks

Mobile sink (MS) has drawn significant attention for solving hot spot problem (also known as energy hole problem) that results from multihop data collection using static sink in wireless sensor networks (WSNs). MS is regarded as a potential solution towards this problem as it significantly reduces energy consumption of the sensor nodes and thus enhances network lifetime. In this paper, we first propose an algorithm for designing efficient trajectory for MS, based on rendezvous points (RPs). We next propose another algorithm for the same problem which considers delay bound path formation of the MS. Both the algorithms use k-means clustering and a weight function by considering several network parameters for efficient selection of the RPs by ensuring the coverage of the entire network. We also propose an MS scheduling technique for effective data gathering. The effectiveness of the proposed algorithms is demonstrated through rigorous simulations and comparisons with some of the existing algorithms over several performance metrics.     

Network lifetime maximization for time‐sensitive data gathering in wireless sensor networks with a mobile sink

With the advances of more and more mobile sink deployments (e.g., robots and unmanned aerial vehicles), mobile sinks have been demonstrated to play an important role in the prolongation of network lifetime. In this paper, we consider the network lifetime maximization problem for time‐sensitive data gathering, which requires sensing data to be sent to the sink as soon as possible, subject to several constraints on the mobile sink. Because the mobile sink is powered by petrol or electricity, its maximum travel distance per tour is bounded. The mobile sink's maximum moving distance from its current location to the next must also be bounded to minimize data loss. As building a new routing tree rooted at each new location will incur an overhead on energy consumption, the mobile sink must sojourn at each chosen location at least for a certain amount of time. The problem, thus, is to find an optimal sojourn tour for the mobile sink such that the network lifetime is maximized, which is subject to a set of constraints on the mobile sink: its maximum travel distance, the maximum distance of each movement, and the minimum sojourn time at each sojourn location. In this paper, we first formulate this novel multiple‐constrained optimization problem as the distance‐constrained mobile sink problem for time‐sensitive data gathering. We then devise a novel heuristic for it. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the performance of the proposed algorithm is very promising, and the solution obtained is fractional of the optimal one. Copyright © 2011 John Wiley & Sons, Ltd.     

Meta‐heuristic algorithms for channel scheduling problem in wireless sensor networks

The channel scheduling problem is to decide how to commit channels for transmitting data between nodes in wireless networks. This problem is one of the most important problems in wireless sensor networks. In this problem, we aim to obtain a near‐optimal solution with the minimal energy consumption within a reasonable time. As the number of nodes increases in the network, however, the amount of calculation for finding the solution would be too high. It can be difficult to obtain an optimal solution in a reasonable execution time because this problem is NP‐hard. Therefore, most of the recent studies for such problems seem to focus on heuristic algorithms. In this paper, we propose efficient channel scheduling algorithms to obtain a near‐optimal solution on the basis of three meta‐heuristic algorithms; the genetic algorithm, the Tabu search, and the simulated annealing. In order to make a search more efficient, we propose some neighborhood generating methods for the proposed algorithms. We evaluate the performance of the proposed algorithms through some experiments in terms of energy consumption and algorithm execution time. The experimental results show that the proposed algorithms are efficient for solving the channel scheduling problem in wireless sensor networks. Copyright © 2011 John Wiley & Sons, Ltd.     

ZCZ‐CDMA and OFDMA using M‐QAM for broadband wireless communications

This paper considers direct‐sequence code‐division multiple‐access with zero‐correlation zone sequences (ZCZ‐CDMA) and orthogonal frequency‐division multiple‐access (OFDMA) schemes using M‐ary QAM signaling for broadband wireless communications. Their system structures, complexities and performances in both AWGN and multipath frequency‐selective fading channels are evaluated and compared. For ZCZ‐CDMA, joint suppression of the multipath fading interference and multiple‐access interference can be achieved with a reduced family‐size of the spreading sequences. For OFDMA, analytical and simulation results indicate that it has the same performance as ZCZ‐CDMA in fast time‐varying multipath fading channels. In time‐invariant or slowly time‐varying channels, where the channel information can be made available to transmitters, OFDMA outperforms ZCZ‐CDMA, offers a higher capacity and is more flexible for system reconfiguration with a comparable computational complexity. Copyright © 2004 John Wiley & Sons, Ltd.     

A lightweight IoT‐based security framework for inventory automation using wireless sensor network

Internet of things (IoT) has evolved as an innovation of next generation in this world of smart devices. IoT tends to provide services for data collection, data management, and data and device security required for application development. Things or devices in IoT communicate and compute to make our lives comfortable and safe. In inventory automation, real‐time check on items, their information management, and status management, monitoring can be carried out using IoT. The huge amount of data that flows among the devices in the network demands for a security framework that ensures authentication, authorization, integrity, and confidentiality of data. The existing security solutions like SIMON or SPECK offer lightweight security solutions but are vulnerable to differential attack because of their simplicity. Moreover, existing solutions do not offer inbuilt authentication. Therefore, this research work contributes a secure and lightweight IoT‐based framework using wireless sensor network (WSN) as a technology. The existing security solutions SPECK and SIMON are compared with the proposed security approach using COOJA simulator. The results show that proposed approach outstands others by 2% reduction in number of CPU cycles, 10% less execution time, 4% less memory requirements of security approach, and with minimum 10% more security impact.     

Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks

Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics.     

A novel chain-based clustering for green communication in wireless sensor network

The rapid growth of the Internet of Things (IoT) creates a high requirement for data collected through wireless sensor networks (WSNs), resulting in a lot of emphasis on WSN data collecting in recent decades. However, the resource-constrained nature of sensor devices exerts heavy constraints for acquiring the optimal network performance. To resolve this concern, this paper proposes the Chain-based Energy-Efficient Clustering (CBEEC) Routing Protocol that considers nodes of two heterogeneous levels of energy (normal level and advanced level). The number of advanced nodes in CBEEC is analytically determined and hence are analytically allocated. However, normal nodes are stochastically deployed in the vicinity of advanced nodes. The data transmission is performed among the advanced nodes in the form of chain and from there it is forwarded to base station (BS). Consequently, it preserves immense amount of energy for the network. The performance of CBEEC is empirically investigated with benchmarks of different performance metrics and simulation outcomes showing that the CBEEC outperforms state-of-the-art routing protocols.     

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

Most of the current generation sensor nodes of mobile wireless sensor network (MWSN) are designed to have heterogeneous mobility to adapt itself in the applied environment. Energy optimization in MWSN with heterogeneous mobility is very challenging task. In this paper, a heterogeneous game theoretical clustering algorithm called mobile clustering game theory–1 (MCGT‐1) is proposed for energy optimization in a heterogeneous mobile sensor environment. Energy optimization is achieved through energy‐efficient cluster head election and multipath routing in the network. A heterogeneous clustering game is modelled with varying attributes and located an asymmetric equilibrium condition for a symmetric game with mixed strategies. The real‐time parameters, namely, predicted remaining energy, distance between a base station and nodes, distance between nodes, and mobility speed, were used to calculate the probability to elect the cluster head (CH). The efficient multipath routing is achieved through prior energy prediction strategy. It has mitigated the generation of “hot spots,” reducing its delay and improving the overall residual energy of the network. Simulation results showed that the average lifetime of MCGT‐1 has increased by 6.33 %, 13.1% and 14.2% and the PDR has improved by 4.8%,11.8%, and 17.2% than MCGT, LEACH‐ME and LEACH‐M respectively. The hot spot delay is reduced to 0.063025 seconds, improving the efficiency of the network.     

E2SRT: enhanced event‐to‐sink reliable transport for wireless sensor networks

An event‐to‐sink reliable transport (ESRT) control scheme was recently proposed to address the event‐to‐sink reliability issues in wireless sensor network (WSN). In this paper, we study the performance of ESRT in the presence of ‘over‐demanding’ event reliability, using both the analytical and simulation approaches. We show that the ESRT protocol does not achieve optimum reliability and begins to fluctuate between two inefficient network states. With insights from update mechanism in ESRT, we propose a new algorithm, called enhanced ESRT (E²SRT), to solve the ‘over‐demanding’ event reliability problem and to stabilize the network. Simulation results show that E²SRT outperforms ESRT in terms of both reliability and energy consumption in the presence of ‘over‐demanding’ event reliability. Besides, it ensures robust convergence in the presence of dynamic network environments. Copyright © 2008 John Wiley & Sons, Ltd.     

A gradient‐based multiple‐path routing protocol for low duty‐cycled wireless sensor networks

Routing in a low duty‐cycled wireless sensor network (WSN) has attracted much attention recently because of the challenge that low duty‐cycled sleep scheduling brings to the design of efficient distributed routing protocols for such networks. In a low duty‐cycled WSN, a big problem is how to design an efficient distributed routing protocol, which uses only local network state information while achieving low end‐to‐end (E2E) packet delivery delay and also high packet delivery efficiency. In this paper, we study low duty‐cycled WSNs wherein sensor nodes adopt pseudorandom sleep scheduling for energy saving. The objective of this paper is to design an efficient distributed routing protocol with low overhead. For this purpose, we design a simple but efficient hop‐by‐hop routing protocol, which integrates the ideas of multipath routing and gradient‐based routing for improved routing performance. We conduct extensive simulations, and the results demonstrate the high performance of the proposed protocol in terms of E2E packet delivery latency and packet delivery efficiency as compared with existing protocols. Copyright © 2014 John Wiley & Sons, Ltd.     

Density‐adaptive network reprogramming protocol for wireless sensor networks

Network reprogramming is a process used to update program codes of sensor nodes that are already deployed. To deal with potentially unstable link conditions of wireless sensor networks, the epidemic approach based on 3‐way advertise‐request‐data handshaking is preferred for network reprogramming. Existing epidemic protocols, however, require a long completion period and high traffic overhead in high‐density networks, mainly due to the hidden terminal problem. In this paper, we address this problem by dynamically adjusting the frequency of advertisement messages in terms of the density of sensor nodes, which is the number of sensor nodes in a certain area. We compare the performance of the proposed scheme, called DANP (Density‐Adaptive Network Reprogramming Protocol), with a well‐known epidemic protocol, Deluge. Simulations indicate that, in the grid topologies, DANP outperforms Deluge by about 30% in terms of the completion time and about 50% in terms of the traffic overhead. Significant performance gain is observed in random topologies as well. The performance of DANP is further confirmed via measurements in an experimental test bed. Copyright © 2009 John Wiley & Sons, Ltd.     

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.     

Graph‐based optimal asynchronous scheduling in large propagation delay underwater acoustic sensor networks

Optimal scheduling is essential to minimize the time wastage and maximize throughput in high propagation delay networks such as in underwater and satellite communication. Understanding the drawbacks of synchronous scheduling, this paper addresses an asynchronous optimal scheduling problem to minimize the time wastage during the transmission. The proposed scheduling problem is analyzed in both broadcast and non‐broadcast networks, which is highly applicable in high propagation delay networks. In broadcast networks, the proposed scheduling method reduces to a graph‐theoretic model that is shown to be equivalent to the classic algorithmic asymmetric traveling salesman problem (TSP) which is NP‐Hard. Although it is NP‐Hard, the TSP is well‐investigated with many available methods to find the best solution for up to tens of thousands of nodes. In non‐broadcast networks, the optimal solution to the scheduling problem considers the possibility of parallel transmission, which is optimized using graph coloring algorithm. The groups obtained through graph coloring are solved using Asymmetric Traveling Salesman algorithm to obtain the optimal schedule. The proposed method efficiently solves the scheduling problem for networks of practical size.     

A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks

Network lifetime maximization is challenging particularly for large-scale wireless sensor networks. The sensor nodes near the sink node tend to suffer high energy consumption due to heavy traffic relay operations, becoming vulnerable to energy depletion. The rationale of the sink mobility approach is that as the sink node moves around, such risk of energy depletion at some nodes can be alleviated. In this paper, we first obtain the optimal mobile sink sojourning pattern by solving a linear programming model and then we mathematically analyze why the optimal solution exhibits such sojourning pattern. We use the insights from this analysis to design a simple practical heuristic algorithm for sink mobility, which utilizes only local information. Our heuristic is very different from the existing algorithms which often use the traffic volume as the main decision factor, in that we consider the variance of residual energy of neighboring sensor nodes. The simulation results show that our scheme achieves near-optimal network lifetime even with the relatively low moving speed of the mobile sink.