Optimal Relay Node Association for Two-Tiered Wireless Networks

The internet of underwater things (IoUTs) is regarded as one of the most technologies in smart oceans that Underwater acoustic sensor networks (UASNs) have recently emerged to support the concept of IoUT. Network lifetime is a vital requirement in UASNs because underwater sensors are supplied with batteries that are difficult to recharge. Relay node placement (RNP) is investigated in recent years to increase the network lifetime that the relay node plays an intermediate node between the critical node and one of its neighbours (i.e., line segment RNP). Due to the tiny feasible region in the line segment RNP, avoiding the redundant relay nodes is a challenging task, especially in the dense UASNs that the distance between nodes is short. In this paper, we design an efficient RNP by defining a threshold distance d<inf>&#x03F5;</inf>. Our objective is to make good tradeoffs between the performance of 3D UASN and complexity in relay-assistance networks. To do this, we introduce a modified difference convex approach (MoDCA). To evaluate our proposed method, we compare it with previous DCA and RIA in terms of the averag number of relay nodes (NoR<inf>a</inf>) and network lifetime through two simulation scenarios.

In this paper we investigate the impact of a Relay Node (RN) placement plan on a heterogeneous wireless network called Hybrid Wireless Network with dedicated delay nodes (HWN*) in terms of system capacity, transmission delay and Quality of Service (QoS). A novel HWN* Heuristic RN Placement (HHRP) algorithm, which considers RN assistance & support for radio resource sharing such as inter-network traffic balancing, TD/CDMA soft handover, routing and user mobility has been implemented. A system level simulation is used to quantify the benefits of HWN* using HHRP algorithm over HWN* with other RN placement plans and multi-hop cellular networks. I. INTRODUCTION A heterogeneous wireless network refers to a wireless net- work that is comprised of wireless nodes with different radio access technologies or equipment with different operating systems. For example, it can be a wireless sensor network including bluetooth based radio access and zigbee 802.15.4 based radio access or a hybrid wireless network including cellular access and 802.11b/g based radio access. Specifi- cally for a hybrid wireless network, the increase of cellular communication intensity results in a reduction in cell size, thus much denser clusters are required resulting in increased infrastructure cost and system complexity. Meanwhile, the bursty nature of communication traffic and path loss results in traffic prediction difficulty. A solution must be found to provide effective resource management, congestion control and routing. The hybrid wireless network which incorporates cellular and MANET interfaced RELAY nodes, provides a practical approach for this. Nevertheless, the dedicated relay infrastructure approach can be also be adapted to the emerging wireless sensor network in order to maintain node connectivity, support sensor data aggregation and optimise power consump- tion.

In the wireless sensor network, an important problem is that how to improve the network lifetime. In recent years, the proposal of using relay nodes to maximize the network lifetime has been suggested in the literature. It is established that, in a two-tiered sensor network (TTSN), higher-power relay nodes which are responsible for receiving and transmitting data can be used as the cluster heads. However, how to extend the network lifetime in a TTSN in this proposal remains a challenge. In this paper, we propose a new approach termed as DSA, to minimize the energy consumption of maximum energy dissipation relay node, which can greatly extend the lifetime of the Two-Tiered Sensor Network. The Main idea is that dividing the relay nodes into several layers at first and then choosing a best transfer path for every relay node at each layer to extend the lifetime of TTSN. We design an algorithm to implement the idea. The advantage of this novel algorithm in terms of complexity and its capability in extending the lifetime of TTSN has been analyzed in detail. By simulations, we compare our method with the direct transmit energy model, minimum transmission energy model and broadcast incremental power algorithm. Simulation results demonstrate significant improvements have been achieved in our method in terms of lifetime of TTSN.

The aim of this article is to develop and implement an optimal method for relay node placement (RNP) to increase lifetime of underwater acoustic sensor networks. Employing a relay node to extend the lifetime of critical node is an important problem in network lifetime maximization, whereas energy consumption of relay node is also a limiting factor. Consequently, maximizing the lifetime of critical node and minimizing consumption of relay node are the two main conflicting objectives that are met by applying the multiobjective optimization. To transform the above objectives into a single objective, weighted sum method is applied, which uses weights. Moreover, the RNP problem investigated in this article is a nonconvex problem, which difference convex algorithm (DCA), is developed in order to compute the optimal solution. Application of DCA offers the advantage of finding a global optimal solution. Simulation results backed by theoretical analysis confirm that the proposed approach is superior to the relay node adjustment method in terms of extending the network lifetime and efficiency, whereas their computational complexity is the same.

In 2tWSN(two-tiered wireless sensor network), relay nodes are responsible for delivering the sensed data from sensor nodes to base stations. From the perspective of business, it needs more relay nodes to ensure network connectivity. From the perspective of economy, relay nodes are relatively expensive, so people are intended to place a minimum number of relay nodes while guaranteeing the data collecting and delivering. In this paper, we firstly model fault tolerant RNP(relay node placement) problem in 2tWSN as a graphic problem, denoted by DBY-HCG. It distinguishes relay nodes from base stations. Secondly, we figure out keCi-RNPB algorithm. Moreover, an approximation algorithm aiming at finding the minimum length of k-vertex disjoint paths in connected sub-graph is raised up to support our algorithm's extensibility. Our algorithm is also the first solution for constrained version of fault tolerant relay node placement problem in 2tWSN. Extensive experiments have been executed in both unconstrained and constrained situations and the numeric results show that our solution is close to optimal solution.

Relay node placement preserving coverage and connectivity is an important problem for the deployment of a fault tolerant two tier wireless sensor network (WSN). In this paper, we propose an algorithm for relay node placement that ensures k-coverage of the sensor nodes and s-connectivity of the relay nodes within the network. The basic goal of the algorithm is to optimize the network cost by using least number of relay nodes. This is carried out by reducing the overlapped coverage area of the relay nodes. The algorithm is based on the spiral traversal of sensor nodes, which is generated by using Jarvis March approach. The proposed algorithm runs in $$O(n^{2})$$ time for n sensor nodes and is shown to be a 1.5-approximation algorithm. It is equally efficient for different and unequal degree of coverage and connectivity in the target area. The algorithm is experimented through the simulation run for different scenarios of WSN. The experimental results are then compared with some existing algorithms to demonstrate its effectiveness.

Relay node placement in wireless sensor networks has potential application value in terms of establishing connected topologies, reducing data latency, and prolonging network life time. This paper studies the relay node placement problem which opts to deploy the optimum number of relay nodes into single-tiered WSN to meet network connectivity. We firstly draw on ideas of Delaunay Triangle and Voronoi Graph to construct neighbor components, then optimize the placement algorithm by means of Spanning tree and Steiner heuristic, finally combine all connected components for connectivity. The experiments show that our proposed algorithm can outperform other algorithms in terms of the number of relay nodes and average hop count with a reasonable time complexity.

An adaptive cuckoo search based algorithm for placement of relay nodes in wireless body area networks

Due to adverse effects of hostile deployment environment(s), sensors nodes (SNs) deployed in the network may drain or get damaged. This attributes for loss of connectivity between the sensors and the sink node. Hence it is necessary to design the wireless sensor network (WSN) in a manner that the network is capable of coping up with the failure of few nodes/links. Using single hop data communication model reduces the lifetime of the network as the SNs are resource constrained (in terms of battery). Relay nodes (RNs) facilitate in improving network lifetime, fault tolerance and/or connectivity. Finding minimum number of relay nodes for a fault tolerant, fully connected network is a NP Hard problem. In this paper, we follow two phase relay node placement procedure to achieve the objective. In the first phase, we cluster the SNs using mean shift algorithm and place RNs as the cluster heads. In the second phase, we use metaheuristic algorithms like Moth Flame Optimization (MFO), Differential Evolution (DE), Bat algorithm (BA) and Biogeography Based Optimization algorithm (BBO) to place the RNs such that the required fault tolerance is achieved along with fully connected network. Extensive simulation results prove that MFO algorithm performs better for fault tolerant relay node placement problem.

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r>0, while relay nodes have communication range Rgesr, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5+epsi)-approximation algorithm for the second problem, where epsi>0 can be any given constant

A wireless sensor network (WSN) is composed of many low cost sensor nodes that can perform sensing, simple computation, and short range communications. To maximize the life time of a WSN, relay nodes are placed to perform communication. In the single-tiered relay node placement problem, the sensor nodes can also participate in the forwarding of the packets of other nodes. In the two-tiered relay node placement problem, only the relay nodes forwards the packets from other nodes. In this talk, we will present the state of the art in the area of relay node placement, ranging from coverage to connectivity and to survivability, and from unconstrained problem to constrained problem. In most cases, efficient approximation algorithms are known.

Delay-tolerant networking (DTN) is an architecture to enable data communications between isolated or remote regions, where long delays and intermittent connectivity can be tolerated. An emerging class of DTN, called vehicular DTNs (VDTN), exploits transportation systems as the transport layer to transfer data. In these networks, vehicles (e.g., busses, boats, trains) act as mobile nodes and carry data messages around. Mobile nodes can exchange data messages using devices called relay nodes. Relay nodes, placed in strategic positions along vehicle routes, have the capability to download, store, and upload the data messages from/to the mobile nodes. An important issue in VDTN is the optimal placement of the relay nodes such that delay-tolerant connectivity in VDTN is ensured at minimum cost. In this paper we show that the problem of optimal relay node placement is an NP-hard problem. Other contributions of this paper are the formulation of the relay node placement problem using ILP and the proposal of heuristic algorithms solving the optimization problem. Using simulation results, we compare the performance of each algorithm under different network constraints, such as node storage capability and network topology.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Device deployment plays a key role in the performance of any large-scale wireless sensor network (WSN) application. WSN device deployment (i.e. the numbers and positions of the devices) must consider several design factors, viz. coverage, connectivity, lifetime, etc. However, connectivity remains the most fundamental factor especially in a large scale harsh environment. In this paper, we explore the problem of relay node (RN) placement in 3D forestry space. We formulate a generalized RN deployment optimization problem aimed at maximizing the network connectivity with constraints on RNs count. We investigate how the number of RNs can affect the connectivity of a WSN in a harsh environment. Based on quantitative analysis of such effects, the paper sets a threshold on the minimum number of required RNs.

For energy-constrained wireless sensor networks (WSNs), the topology control issue is fundamental and important to maximize the overall network lifetime. Recently a two-tiered network model has been proposed for this purpose. It is a cluster-based network model composed of application and sensor nodes. In this model the application nodes are easy to run out of energy because they not only serve as cluster heads for aggregating data packets from the sensor nodes in their clusters but also are responsible for forming a connected network topology for information dissemination at the higher tier. In order to balance nodes' power consumption and extend the topological lifetime of a WSN with regard to a certain amount of initial energy provision, we propose a logical three-tiered network model which consist of relay nodes (RNs), application nodes (ANs) and sensor nodes (SNs). Under this architecture, the goal of lower-tier SNs is to sense the playing fields and middle-tier ANs only need to gather data from their clusters; Upper-tier RNs are designed to route information as efficiently as possible. In this paper, we first formulate the three-tiered WSN's model as well as the power consumption model of WSNs. Then considering one dimension relaying, we figure out the RNs' optimal placement for each AN which can considerably minimize the total power consumption for WSNs. Finally, we give some criteria for two-dimension relaying.