Partitioned Wireless Sensor Networks Research Articles

Nature-inspired donkey and smuggler algorithm for optimal data gathering in partitioned wireless sensor networks for restoring network connectivity

Nature-inspired donkey and smuggler algorithm for optimal data gathering in partitioned wireless sensor networks for restoring network connectivity

Obstacle-aware connectivity restoration for the partitioned wireless sensor networks using mobile data carriers

Obstacle-aware connectivity restoration for the partitioned wireless sensor networks using mobile data carriers

An efficient data collection algorithm for partitioned wireless sensor networks

Data collection with mobile agent (MA) can balance the energy consumption of nodes in partitioned wireless sensor networks. However, the existing data collection algorithms for partitioned WSNs do not formalize the problem systematically. These algorithms are not efficient and difficult to meet the timeliness requirement. In order to solve the above shortcomings, we first formalize the Data Collection Problem (DCP). Then, it is transformed into a Generalized Traveling Salesman Problem (GTSP), and we propose a GTSP-Based data collection Algorithm (GBA) to calculate the rendezvous points (RPs) and the moving path of MA. GBA selects RPs by solving the GTSP problem. Furthermore, based on GBA, we take advantage of constructing convex hull to plan a more efficient moving path for MA. In addition, in order to reduce the energy burden on the RPs, we design an Improved Shortest Path tree (ISP tree) to aggregate data from nodes to RPs in partitioned WSNs. Finally, extensive simulations demonstrate the effectiveness and advantages of our algorithm in terms of the length of MA’s moving path and the amount of data collection per unit time.

Toward connectivity of a disconnected cluster in partitioned wireless sensor network for time-critical data collection

Reliable network connectivity is one of the major design issues in the context of wireless sensor networks. These networks have diverse communication patterns due to non-uniform sensing activities at various locations in the environment being monitored. In such scenarios, some nodes lying in high-traffic zones may consume more energy and eventually die out resulting in network partitioning. This gives rise to a situation in which alive nodes are trapped in a disconnected cluster, and they do not have enough radio range to communicate their data to the destination (i.e. a sink or a relay node connected to the main part of the network). This phenomenon may deprive a large number of alive nodes of sending their important time-critical data to the sink. In this article, we propose a virtual antenna–based cooperative beamforming approach for retrieving valuable data from these disconnected nodes. In the proposed approach, the sensor nodes in an isolated partition work together to form a directional beam. This directional beam significantly increases their overall communication range to reach out to a distant relay node which is connected to the main part of the network. The proposed approach of cooperative beamforming–based partition connectivity is more effective when a cluster with a favorably large number of nodes gets partitioned. Furthermore, a beamforming-based mechanism is proposed for a disconnected cluster to locate the nearest relay node which is still connected to the sink and to reconnect itself to the main part of the network via the most adjacent relay node for time-critical data transmission. The proposed mechanism is then evaluated through simulation results.

Round-table negotiation for fast restoration of connectivity in partitioned wireless sensor networks

This paper addresses the problem of restoration of connectivity in wireless sensor networks after multiple simultaneous node failures. Such failures of multiple nodes may split the network into several clusters. These clusters are unaware of their own size, surviving nodes and links as well as size and location of other survivor clusters. A distributed and autonomous approach of reconnecting disjoint clusters in a short time is proposed, in which each survivor cluster undergoes a self-discovery process where it compiles information of connected survivors and then sends a negotiator to participate in a round table negotiation and decision-making process. All such negotiators exchange information and decide upon reconnection paths between clusters through known dead node locations and then assign nodes to be deployed on those paths, using available nodes. The negotiators then return to their respective clusters, convey the decision and the reconnection process is carried out. Analytical results of the self-discovery process have been obtained and simulation results on a large network are presented to illustrate the process. It is shown through a detailed comparison with existing methods that the proposed approach achieves reconnection in significantly lower time and compares favorably with respect to other performance metrics as well.

Survivability-Aware Connectivity Restoration for Partitioned Wireless Sensor Networks

In this letter, we propose a survivability-aware connectivity restoration strategy for partitioned wireless sensor networks with mobile nodes. Our main contributions lie in two aspects. First, we design a load equilibrium mechanism, in which the partitioned segments are connected according to an in-order connection pattern rather than conventional factors, so as to enhance the network lifespan. Second, we design a reliability enhancement measure, in which the stopping points of mobile nodes are selected according to the surrounding node distribution status rather than conventional factors, so as to reduce the connectivity failure probability for the second destruction. In the end, simulations are conducted to demonstrate the effectiveness and advantages of our connectivity restoration scheme.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Multi-criteria Routing in a Partitioned Wireless Sensor Network

Energy efficiency is one of the key challenges for designing routing algorithms for wireless sensor networks (WSN). Fast data delivery from source node to sink node is also required for many applications. Sometimes data transmission towards the sink may be interrupted because of failure of nodes in a particular area. The various such requirements of routing data in a WSN are sometimes contradictory and routing algorithms must be designed keeping in mind all these requirements. In this paper three routing algorithms are proposed for multi-sink partitioned network. In these three algorithms, the source nodes or intermediate nodes select a next node to forward the data to the destination or sink. This process repeats until the data reaches the sink. In the first technique, the next node is chosen considering its distance from sink node as a criterion. In the second technique, remaining energy of the neighboring nodes is used as a criterion for selection of the next node. The combination of these two criteria is considered in the third technique and a multiple criteria decision analysis technique is used. A recovery technique from area failure is also proposed and incorporated in the above mentioned algorithms. The algorithms are designed and implemented in multi-sink environment for partitioned wireless sensor networks. Performances of the algorithms are studied in a simulation environment and compared with other well-known algorithms to understand their effectiveness.

Mobile Relay Scheduling in Partitioned Wireless Sensor Networks

In a wireless sensor network (WSN), sensors collect data that need to be delivered to a base station. This requires that the WSN should be a connected network. However, due to possible failures of sensors, a WSN might be partitioned into multiple isolated blocks. A solution to reconnect the WSN is to deploy mobile relays in the WSN and to schedule the mobile relays to positions that can reconnect the isolated blocks. In this paper, we target at a mobile relay scheduling (MRS) algorithm with the minimal total movement cost such that the partitioned WSN becomes connected. We give a definition for boundary sensors of blocks and show that, to connect two blocks, fewer mobile relays are used if we connect the two blocks through a pair of their boundary sensors. To connect a given pair of boundary sensors from two blocks, we derive the optimal new positions of mobile relays, which minimize the total energy consumption of mobile relays when relaying information between the two blocks. To connect a partitioned WSN with multiple isolated blocks, an MRS problem is formulated and shown to be NP-complete. Then, a greedy MRS algorithm is proposed to select boundary sensor pairs and reconnect the WSN by scheduling mobile relays to optimal new positions of connecting the selected boundary sensor pairs. Since the selected boundary sensors are gateways of blocks and the moved mobile relays serve as routers to connect the blocks, any failure of them may disconnect the WSN again. Accordingly, another greedy MRS algorithm is proposed to reconnect a partitioned WSN such that the reconnected WSN can tolerate failure of one gateway or one router. Extensive simulations demonstrate that the proposed algorithms have better performance over other existing methods in terms of higher success probability and less movement cost.

Restoration of lost connectivity of partitioned wireless sensor networks

Abstract The lost connectivity due to failure of large-scale nodes plays major role to degrade the system performance by generating unnecessary overhead or sometimes totally collapse the active network. There are many issues and challenges to restore the lost connectivity in an unattended scenario, i.e. how many recovery nodes will be sufficient and on which locations these recovery nodes have to be placed. A very few centralized and distributed approaches have been proposed till now. The centralized approaches are good for a scenario where information about the disjoint network, i.e. number of disjoint segments and their locations are well known in advance. However, for a scenario where such information is unknown due to the unattended harsh environment, a distributed approach is a better solution to restore the partitioned network. In this paper, we have proposed and implemented a semi-distributed approach called Relay node Placement using Fermat Point. The proposed approach is capable of restoring lost connectivity with small number of recovery relay nodes and it works for any number of disjoint segments. The simulation experiment results show effectiveness of our approach as compared to existing benchmark approaches.

Connectivity restoration in a partitioned wireless sensor network with assured fault tolerance

Wireless sensor network (WSN) applications, especially those serving in inhospitable environments such as battlefield reconnaissance, are susceptible to large-scale damage which usually causes simultaneous failure of multiple collocated sensors and gets the network divided into disjoint partitions. In order to prevent the WSN from being inoperative, restoring the overall network connectivity is crucial. Furthermore, it may be desirable to make the repaired network topology resilient to future single node failures caused by aftermath. In this paper, we present an effective strategy for achieving such recovery goal by establishing a bi-connected inter-partition topology while minimizing the maximum path length between pairs for partitions and deploying the least count of relay nodes (RNs). Finding the optimal number and position of RNs is NP-hard and we thus pursue heuristics. The proposed Connectivity Restoration with Assured Fault Tolerance (CRAFT) algorithm strives to form the largest inner simple cycle or backbone polygon (BP) around the center of the damaged area where no partition lies inside. RNs are then deployed to connect each outer partition to the BP through two non-overlapping paths. We analyze the properties of CRAFT mathematically and validate its performance through extensive simulation experiments. The validation results show that CRAFT yields highly connected topologies with short inter-partition paths while employing fewer RNs than competing schemes.

Relay placement for restoring connectivity in partitioned wireless sensor networks under limited information

Several factors such as initial deployment, battery depletion or hardware failures can cause partition wireless sensor networks (WSNs). This results in most of the sensors losing connectivity with the sink node and thus creating disruption of the delivery of the data. To restore connectivity, one possible solution is populating relay nodes to connect the partitions. However, this solution requires information regarding the availability of the damaged area, number of partitions in the network and the location of the remaining nodes which may not be obtained for all applications. Thus, a distributed self-deployment strategy may better fit the application requirements. In this paper, we propose two distributed relay node positioning approaches to guarantee network recovery for partitioned WSNs by minimizing the movement cost of the relay nodes. The first approach is based on virtual force-based movements of relays while the second exploits Game Theory among the leaders of the partitions. Force-based approach stretches the network gradually with the deployment of additional relays. In the game-theoretic approach, the partition to be connected with is determined by the leader relay nodes based on the probability distribution function (pdf) of the partitions. Partitions with a higher pdf have priority over other partitions for recovery. Once the partition is connected with the relay nodes, it becomes the part of the connected network. Recovery proceeds with the partition having the next highest priority until network is completely recovered by reaching the system-wide unique Nash equilibrium. Both approaches are analyzed and evaluated extensively through simulation. Game-theoretic approach has been shown to outperform force-based approach as well as a centralized approach under most of the conditions.