Multi-hop Manner Research Articles

Joint Data Collection and Fusion Using Mobile Sink in Heterogeneous Wireless Sensor Networks

Using a mobile sink for data collection from the sensors has been considered as a good way to prolong the network lifetime of wireless sensor networks (WSNs). To avoid the problems of long delay and data non-fresh, some previous studies selected a set of data collection points (CPs) and all the other sensors transmit their data to the closest CP in a multi-hop manner. Then the mobile sink only needs to visit and collect data from the selected CPs, reducing the path length of the mobile sink and the time required for collecting data from all sensors. This paper proposes a data collection mechanism, called DDCF, which uses a mobile sink to collect data in a heterogeneous WSN(HWSN), aiming to prolong the network lifetime while improving the surveillance coverage. The proposed DDCF mainly consists of CP selection and tree topology construction phases in each round. The CP selection phase takes into consideration multiple parameters including remaining energy, coverage contribution as well as data fusion degree and then dynamically selects CPs in each round for balancing the lifetime of CPs and improving the surveillance quality. In the tree topology construction phase, each sensor selects its parent by considering the remaining energy, data fusion degree and transmission success ratio, which aims to dynamically construct a tree topology for further reducing and balancing the energy consumptions of sensor nodes. Performance study shows that the proposed DDCF outperforms existing studies in terms of network lifetime, fairness as well as surveillance quality.

Fuzzy Tree Clustering Algorithm with Mobile Data Collectors in Wireless Sensor Networks

In recent years, the need to deploy Wireless Sensor Networks increases in different applications. Several studies have been proposed to demonstrate the importance to use Mobile Data Collectors (MDC) in Wireless sensor Networks. The main goal of this paper is to reduce the energy consumption of sensor nodes and to extend the network lifetime. In this paper, we propose to construct a Minimum Spanning tree, we design a fuzzy Cluster Head election system to elect the best sensor nodes as Cluster Heads, considering two input parameters, namely the weight of Sensor Nodes (WoSN) and the State of Sensor Node Locations (SoSNLoc). To extend the network lifetime, a subset of MDCs travels the area to gather the sensed data from nodes instead of sending them directly to the Base Station (BS) in a single hop or multi-hop manner. The BS is located at the center of the area which will be divided into sub-regions, one for each MDC. According to their positions, each CH will belong to a specific region, and then will be visited by the corresponding MDC. Simulation results show the effectiveness of our proposed algorithm in terms of energy consumption and network lifetime in comparison with other ones.

Securing Cyber-Physical Systems from Hardware Trojan Collusion

Hardware Trojans, which are malicious modifications made to circuits, may cause severe security issues in Cyber-Physical Systems (CPS). CPS are usually composed of multiple untrusted nodes and a trusted server, with each node connecting to the server wirelessly in a multi-hop manner. A Trojan in one node may broadcast messages with triggers secretly embedded to simultaneously activate multiple Trojans in other nodes, causing system-wide catastrophe. To prevent hardware Trojan collusion in CPS, this paper presents a collaborative defensive framework. When deploying the network, a security requirement of vendor diversity is enforced between neighboring nodes, thus precluding collusion between neighboring nodes and allowing them to monitor each other's behavior. At runtime, a mutual auditing protocol is utilized to check, for each message, whether it is correctly encrypted by the source node and whether its content is maliciously changed by any node on the routing path. This protocol ensures that any message embedded with hardware Trojan trigger is either muted or detected and abandoned, while the benign messages are thwarted. The experimental results show that the framework effectively prevents hardware Trojan collusion with low latency overhead and almost no impact on packet completion rate and network throughput.

A cost-efficient elastic UAV relay network construction method with guaranteed QoS

Recently, Unmanned Aerial Vehicle (UAVs) have been widely adopted to collect data in dangerous or inaccessible areas due to their unique characteristics, including on-demand deployment, flexibility, low-cost, and mobility. However, limited power supply severely restricts the transmission range of a UAV, thus the sensed data needs to be transmitted to the ground control station (GCS) with the help of multiple UAVs in a multi-hop manner. This paper firstly describes the general process of the UAV relay network deployment, and analyzes the number of relay UAVs needed by two types of straightforward static model, i.e. track-based dynamic routing model with planned path and the infrastructure-based dynamic routing model with uncertain path. Deploying the relay UAVs in a static way as current works do cannot fulfill the requirements for an ideal UAV relay network, such as high reliability, low-cost and guaranteed quality of service. Thus, we detail our prediction-based dynamic relay network deployment model, and prove that our proposal is feasible and requires less number of relay UAVs while providing higher communication quality compared with state-of-the-art methods. Based on this model, an Elastic Relay Network Construction (ERNetC) algorithm is proposed. Finally, a series of simulation experiments are conducted on OMNeT++ simulation platform to evaluate the performance of ERNetC algorithm. Simulation results show that ERNetC algorithm outperforms existing algorithms in total interruption time as well as goodput.

Adaptive directed evolved NSGA2 based node placement optimization for wireless sensor networks

Wireless sensor network (WSN) is a wireless network composed of a large number of static or mobile sensors in a self-organizing and multi-hop manner. In WSN research, node placement is one of the basic problems. In view of the coverage, energy consumption and the distance of node movement, an improved multi-objective optimization algorithm based on NSGA2 is proposed in this paper. The proposed algorithm is used to optimize the node placement of WSN. The proposed algorithm can optimize both the node coverage and lifetime of WSN while also considering the moving distance of nodes, so as to optimize the node placement of WSN. The experiments show that the improved NSGA2 has improvements in both searching performance and convergence speed when solving the node placement problem.

Collaborative energy efficient zone‐based routing protocol for multihop Internet of Things

ABSTRACTIn Internet of Things (IoT) the nodes collaborate over a network in multihop manner and relay data toward IoT gateway that is ultimately connected to an IP network. The conventional multihop routing protocols assume that all nodes behave truthfully when they receive packets for downstream network but in reality, the IoT relaying nodes avoid message forwarding. The main reason of selfish behavior of nodes is the limited battery power. Many such nodes have limited battery constraint so these nodes may become selfish to save their energy. These nodes need to be encouraged to cooperate in order to increase network life time instead of just trying to increase node's own benefits. This paper discusses energy aware zone‐based routing technique that employs game theory to enhance nodes' cooperation and energy efficiency. The nodes follow a path with highest average energy for communication and provide collective support, hence the network life time is increases. For comparative analysis, simulation is performed for the proposed technique along with the existing techniques. The results show betterment in throughput, packet delivery ratio, and network life time.

A Distributed Framework for Task Offloading in Edge Computing Networks of Arbitrary Topology

An important issue in an edge computing (EC) network is to increase the utilities of the end users concurrently accessing the computation resources. In this paper, we consider the task offloading in EC-enabled networks where the end users efficiently utilize the dispersed computation and communication resources in a multi-path multi-hop manner. We propose a binary optimization framework that generalizes multi-hop wireless EC task offloading as jointly making decisions of server selecting and traffic routing in networks of arbitrary topology ( JoSRAT ). We further develop an approximation algorithm JoSRAT that enables for a fully distributed implementation together with the worst-case performance guarantees. Interestingly, our proposed distributed algorithm achieves nearly optimal in the numerical evaluations, significantly outperforming the worst-case guarantees. The proposed algorithm also outperforms a widely-used heuristic, i.e., First Fit, in terms of computational time complexity, indicating the superior capability of the proposed framework.

A new software-defined network architecture to solve energy balance problems in wireless sensor networks

Wireless sensor networks (WSNs) are an important part of the internet of things. In WSNs, the sensor battery is limited, and the entire network has a data aggregation node called Sink. When the sensor transmits data to the Sink in a multi-hop manner, the sensors around the Sink also help other sensors to forward the data to the Sink. This causes those sensors to die faster than other sensors. This problem is called energy hole problem. Previous solutions such as sensor uneven distribution schemes and clustering schemes are not only difficult to implement, but also increase the design cost of the system. In particular, traditional WSNs cannot be updated once deployed. In order to solve the above problem, we propose a method of combining SDN and WSNs. The simulation results show that the proposed method has good performance in terms of the number of surviving sensors, network capacity and residual energy.

A new software-defined network architecture to solve energy balance problems in wireless sensor networks

Wireless sensor networks (WSNs) are an important part of the internet of things. In WSNs, the sensor battery is limited, and the entire network has a data aggregation node called Sink. When the sensor transmits data to the Sink in a multi-hop manner, the sensors around the Sink also help other sensors to forward the data to the Sink. This causes those sensors to die faster than other sensors. This problem is called energy hole problem. Previous solutions such as sensor uneven distribution schemes and clustering schemes are not only difficult to implement, but also increase the design cost of the system. In particular, traditional WSNs cannot be updated once deployed. In order to solve the above problem, we propose a method of combining SDN and WSNs. The simulation results show that the proposed method has good performance in terms of the number of surviving sensors, network capacity and residual energy.

SLGBM: An Intrusion Detection Mechanism for Wireless Sensor Networks in Smart Environments

Wireless sensor network (WSN), which serves as one of the key components of the cyber physical system, is a wireless network composed of many stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes and transmits the information of the perceived objects in the geographical area covered by the network, and finally sends this information to the owner of the network. There are some typical attacks in WSN, such as Blackhole, Grayhole, Flooding and Scheduling attacks, which may cause damages to the WSN system in a short time. Moreover, intrusion detection methods for WSN suffer from the disadvantages of low detection rate, large calculation overhead, and high false alarm rate due to the limited resources of sensor nodes and a large amount of redundancy as well as high correlation of network data. In view of the above problems, we propose SLGBM, an intrusion detection method for wireless sensor networks. First, the sequence backward selection (SBS) algorithm is applied to reduce the data dimension on the feature space of the original traffic data so as to reduce the computational overhead. A LightGBM algorithm is then utilized to detect different network attacks. The experimental results based on the WSN-DS dataset show that F-measure of our proposed SLGBM are obviously superior to current typical detection methods, which are 99.8%, 99.4%, 99.1%, 96.5%, and 96.1% in Normal, Blackhole, Grayhole, Flooding, and Scheduling (TDMA) attack detections respectively.

New Approach of Energy-Efficient Hierarchical Clustering Based on Neighbor Rotation for RWSN

Energy Efficient Hierarchical Clustering (EEHC) method is a distributed random clustering algorithm for residential wireless sensor networks (RWSNs) with the goal of maximizing network lifetime. However, during selection of the cluster head stage, a node declares itself as a cluster head to neighboring nodes with probability p, which does not consider well the topological characteristics of the network. The new energy-efficient hierarchical clustering approach based on neighbor rotation (EEHCN) for RWSN has been proposed in this paper, the new idea of which determines whether a node of RWSN can become a cluster head node by comparing the comprehensive weighting of the degree of the sensor node and the distance between the sensor node and the center of the subarea. When the cluster head is replaced, a member node in the set of neighbor nodes of the current cluster head becomes the new cluster head for a random time slice, and the merged information is transmitted to the nearest sink node in a multi-hop manner according to the routing information. The experimental results demonstrate that the proposed method is more effective in saving network energy, improving data transmission efficiency, and maximizing network lifetime of RWSN. The innovative research work is very useful for the relative application of the RWSN, such as smart home or smart community.

A Composite Model for an Intelligent Device-To-Device Communication in the Internet of Things

Similar to how humans communicate, devices will have to communicate with each other in the Internet of Things (IoT) ecosystem. Where the devices themselves become the users of the knowledge or the data that is acquired. Hence we can say that device-to-device communication becomes an intrinsic part of IoT. Devices have to communicate autonomously with each other without any centralized monitoring system. It will be more powerful when the devices can communicate in a multi-hop manner rather than a single-hop manner where the information when and where needed can be accumulated and used. This leads to a need where there must be a group communication between the devices in a particular network. Hence information about the network and the environment in which the devices operate can be identified and the relevant knowledge can be transferred to a peer network or a device for further information gathering or the peer nodes can be used as intermediate nodes in the multi-hop network. Here we are proposing a network of multi-hop interconnected intelligent IoT devices that can communicate among its peer devices gather information and send the information in a multi-hop fashion making using of the adjacent networks or clusters.

Performance Analysis of Ad-Hoc Networks using Statistic Mechanics

An ad-hoc network is an interconnection of source node and destination node pairs with wireless communication, and it is non-centralized manner, nodes are having self-organizing capabilities. The nodes can move dynamically in such a way that interconnection between nodes vary. The routing mechanism in these networks is in multi-hop manner by taking help of intermediate nodes, these nodes helps in packet flow between source and destination node. Advantage of this type of routing is conservation of energy and efficiently delivers packets. This multi-hop manner of packet transmission introduces blending of various traffic flows, resulting in inter-dependencies between activities of nodes and strong correlations among the nodes. The analysis of ad-hoc networks is complicated task; techniques of the information theory will not yield an accurate analysis. In this work, we use a sub field of statistic mechanics called Totally Asymmetric Simple Exclusion Process and MAC technique for evaluating ad-hoc networks. This helps in evaluating performance parameters such as average delay and throughput of linear ad-hoc network. Finally it has been demonstrated that TASEP can improve the performance parameter such as end to end delay and throughput.

Hierarchical Network Architecture for Non-Safety Applications in Urban Vehicular Ad-Hoc Networks

In the vehicular ad-hoc networks (VANETs), wireless access in vehicular environments (WAVE) as the core networking technology is suitable for supporting safety-critical applications, but it is difficult to guarantee its performance when transmitting non-safety data, especially high volumes of data, in a multi-hop manner. Therefore, to provide non-safety applications effectively and reliably for users, we propose a hybrid V2V communication system (HVCS) using hierarchical networking architecture: a centralized control model for the establishment of a fast connection and a local data propagation model for efficient and reliable transmissions. The centralized control model had the functionality of node discovery, local ad-hoc group (LAG) formation, a LAG owner (LAGO) determination, and LAG management. The local data propagation indicates that data are transmitted only within the LAG under the management of the LAGO. To support the end-to-end multi-hop transmission over V2V communication, vehicles outside the LAG employ the store and forward model. We designed three phases consisting of concise device discovery (CDD), concise provisioning (CP), and data transmission, so that the HVCS is highly efficient and robust on the hierarchical networking architecture. Under the centralized control, the phase of the CDD operates to improve connection establishment time, and the CP is to simplify operations required for security establishment. Our HVCS is implemented as a two-tier system using a traffic controller for centralized control using cellular networks and a smartphone for local data propagation over Wi-Fi Direct. The HVCS’ performance was evaluated using Veins, and compared with WAVE in terms of throughput, connectivity, and quality of service (QoS). The effectiveness of the centralized control was demonstrated in comparative experiments with Wi-Fi Direct. The connection establishment time measured was only 0.95 s for the HVCS. In the case of video streaming services through the HVCS, about 98% of the events could be played over 16 frames per second. The throughput for the streaming data was between 74% to 81% when the vehicle density was over 50%. We demonstrated that the proposed system has high throughput and satisfies the QoS of streaming services even though the end-to-end delay is a bit longer when compared to that of WAVE.

Evaluation of Data Compression Techniques for Video Transmission over Wireless Sensor Networks

Video transmission over WSN is a challenging task because, video data is inherently huge in size and its transmission requires high bandwidth and processing requires more memory and more power. Presently majority of the research work in this area is focused on improving battery life, optimizing network parameters and increasing energy efficiency. The area of best suitable compression scheme for WSN is rarely being explored. This paper focuses on finding out a suitable compression technique for video transmission over WSN. Wireless sensor network (WSN) is an ad-hoc network of sensor nodes, where each node is able to communicate with every other node in the network in single hop or multi-hop manner. It is a low cost, low power and low bandwidth network with each node having limited battery life and limited memory. In order to overcome these challenges, initially image compression is applied on each frame extracted from given video. To find out most suitable compression technique for WSN, the various existing 2D image transforms like DCT, KLT, Slant, Hartley, Hadamard and DST are compared based upon their energy compaction property. The transform that gives more energy compaction is best suitable for WSN. Thus, after selecting a suitable transform for WSN domain, it is applied to obtain compressed video frames. Zigbee protocol based hardware setup is used for serial transmission of RGB video data frames between the nodes. Different parameters are evaluated for received image frames and transmitted image frames. Experimental evaluation shows that zigbee hardware set up improves the reliability and efficiency of video data transmission. This type of WSN set-up can be used for capturing video in any remote and hard-lying (border, mountains, forest) area, where any other types of networks are not available.

Confidentiality Protecting Hierarchical Concealed Data Aggregation for Wireless Sensor Network using Privacy Homomorphism

A Wireless Sensor Network is a set of sensor nodes that are integrated with a physical environment. This tiny sensor node capable of sensing physical phenomena and it can process the sense data. Sensor nodes radio range is short so they transfer data in a multihop manner to form network which will send network activities to base station. Data transmission consumes much more energy than computation. So to overcome this problem data aggregation technique can be useful. This approach reduces energy consumption by avoiding repeated data. Security in wireless sensor network is also one of the important issues. Some properties of a WSN make it more harmed by certain types of attackers, compared to traditional wired network. Furthermore, constrained devices create their own problems for wireless sensor network. As sensor node is powered by batteries and node required lot of energy to perform some complex computation. So it is important to prevent every node in computation process which will save energy to gain longer network life. The focus of this work is provides confidentiality protecting hierarchical concealed data aggregation for WSN using privacy homomorphism. End to End Homomorphic Paillier cryptoscheme is used to achieve proposed approach.

Routing and Clustering of Sensor Nodes in the Honeycomb Architecture

Energy is the most valuable resource in wireless sensor networks; this resource is limited and much in demand during routing and communication between sensor nodes. Hierarchy structuring of the network into clusters allows reducing the energy consumption by using small distance transmissions within clusters in a multihop manner. In this article, we choose to use a hybrid routing protocol named Efficient Honeycomb Clustering Algorithm (EHCA), which is at the same time hierarchical and geographical protocol by using honeycomb clustering. This kind of clustering guarantees the balancing of the energy consumption through changing in each round the location of the cluster head, which is in a given vertex of the honeycomb cluster. The combination of geographical and hierarchical routing with the use of honeycomb clustering has proved its efficiency; the performances of our protocol outperform the existing protocols in terms of the number of nodes alive, the latency of data delivery, and the percentage of successful data delivery to the sinks. The simulations testify the superiority of our protocol against the existing geographical and hierarchical protocols.

A Novel Hybrid Opportunistic Scalable Energy Efficient Routing Design for Low Power, Lossy Wireless Sensor Networks

Opportunistic Routing (OR) scheme increases the transmission reliability despite the lossy wireless radio links by exploiting the broadcast nature of the wireless medium. However, OR schemes in low power Wireless Sensor Network (WSN) leads to energy drain in constrained sensor nodes due to constant overhearing, periodic beaconing for Neighbourhood Management (NM) and increase in packet header length to append priority wise sorted Forwarding Candidates Set (FCS) prior to data transmission. The timer-based coordination mechanism incurs the least overhead to coordinate among the FCS that has successfully received the data packet for relaying the data in a multi-hop manner. This timer-based mechanism suffers from duplicate transmissions if the FCS is either not carefully selected or coordinated. The focus of this work is to propose a hybrid opportunistic energy efficient routing design for large scale, low power and lossy WSN. This design avoids periodic 'hello' beacons for NM, limits constant overhearing and increase in packet header length. There are two modes of operation i) opportunistic ii) unicast mode. The sender node adopts opportunistic forwarding for its initial data packet transmission and instead of pre-computing the FCS, it is dynamically computed in a completely distributed manner. The eligible nodes to be part of FCS will be neighbour nodes at lower corona level than the sender with respect to the sink and remaining energy above the minimum threshold. The nodes part of FCS based on crosslayered multi-metrics and fuzzy decision logic determines its priority level to compute Dynamic Holding Delay (DHD) for effective timer coordination. The differentiated back off implementation along with DHD enables the higher priority candidate that had received data packet to forward the packet first and facilitates others to cancel its timer upon overhearing. The sender node switches to unicast mode of forwarding for successive transmissions by choosing the forwarding node with maximum trust value as it denotes the stability of the temporally varying link with respect to the forwarder. The sender node will revert to opportunistic mode to increase transmission reliability in case of link-level transmission error or no trustworthy forwarders. Simulation results in NS2 show significant increase in Packet Delivery Ratio (PDR),decrease in both average energy consumption per node and Normalized Energy Consumption (NEC) per packet in comparison with existing protocols.

A Robust Energy Saving Data Dissemination Protocol for IoT-WSNs

In Wireless Sensor Networks (WSNs) for Internet of Things (IoT) environment, fault tolerance is a most fundamental issue due to strict energy constraint of sensor node. In this paper, a robust energy saving data dissemination protocol for IoT-WSNs is proposed. Minimized energy consumption and dissemination delay time based on signal strength play an important role in our scheme. The representative dissemination protocol SPIN (Sensor Protocols for Information via Negotiation) overcomes overlapped data problem of the classical Flooding scheme. However, SPIN never considers distance between nodes, thus the issue of dissemination energy consumption is becoming more important problem. In order to minimize the energy consumption, the shortest path between sensors should be considered to disseminate the data through the entire IoT-WSNs. SPMS (Shortest Path Mined SPIN) scheme creates routing tables using Bellman Ford method and forwards data through a multi-hop manner to optimize power consumption and delay time. Due to these properties, it is very hard to avoid heavy traffic when routing information is updated. Additionally, a node failure of SPMS would be caused by frequently using some sensors on the shortest path, thus network lifetime might be shortened quickly. In contrast, our scheme is resilient to these failures because it employs energy aware concept. The dissemination delay time of the proposed protocol without a routing table is similar to that of shortest path-based SPMS. In addition, our protocol does not require routing table, which needs a lot of control packets, thus it prevents excessive control message generation. Finally, the proposed scheme outperforms previous schemes in terms of data transmission success ratio, therefore our protocol could be appropriate for IoT-WSNs environment.

MLBC: Multi-objective Load Balancing Clustering technique in Wireless Sensor Networks

In Wireless Sensor Networks (WSN) there are scenarios with conflicting objectives. This needs to be modeled as multi-objective optimization formulation. The optimization problem changes with the nature of application, network scenario and input/output parameters. Depending upon the underlying application requirements, there is a need of an appropriate Multi-Objective Optimization technique to manage these multiple conflicting objectives simultaneously and to yield an overall optimal solution. In this paper, a novel Multi-objective Load Balancing Clustering (MLBC) technique is proposed by utilizing Multi Objective Particle Swarm Optimization (MOPSO). Two objective functions are defined: Energy Efficiency and Reliability. The energy efficiency is based on the average residual energy of Cluster Heads (CHs), whereas the reliability is based on the communication cost of inter-cluster routing. The nodes transmit their information to Cluster Head or Base Station in single-hop or multi-hop manner. A healing function is utilized to avoid loops in the generated path. The load balancing is performed by shuffling the roles of next hop node and Cluster Head in each iteration. The best compromise solution is selected through the fuzzy decision-based approach. The performance of the proposed and existing approaches has been evaluated in terms of energy efficiency, network lifetime, packet delivery ratio, data accuracy and number of active nodes. Apart from these parameters, coverage and scalability are also considered to evaluate the quality of solutions provided by multi-objective optimization approach.