Dynamic data aggregation protocol based on multiple objective tree in Wireless Sensor Networks

This paper considers the problem of jointly constructing and scheduling forwarding trees in a wireless sensor network, each for a group of sensor nodes, to collect measurements at a single sink node. The goal is to construct such trees which gather measurements in the most energy efficient manner and minimal gathering latency. We assume transmissions (carrying measurements) on wireless links interfere with one another, and thus appropriate link scheduling is required to overcome interference. We refer to this problem as Forwarding Tree Construction and Scheduling (FTCS). Each tree may be constructed independently and then its links are scheduled. However, when all trees are combined together, the shortest and energy efficient schedule may not be guaranteed. Further, a large number of possible forwarding trees for each group of sensors may be considered. Both problems of enumerating forwarding trees and scheduling links for those trees are hard combinatorial problems. This is compounded by the fact that the two problems must be solved jointly, to guarantee the selection of best forwarding trees which, when their links are scheduled, guarantee a shortest energy efficient schedule. After highlighting the complexity of the FTCS problem, we present a novel primal-dual decomposition method using column generation. We also highlight several challenges we faced when solving the decomposed problem and present efficient techniques for mitigating those challenges. One major advantage of our work is that it can serve as a benchmark for evaluating the performance of any low complexity method for solving the FTCS problem for larger network instances where no known exact solutions can be found.

Tree-based routing structures are widely used to gather data in wireless sensor networks. Along with tree structures, in-network aggregation is adopted to reduce transmissions, to save energy and to prolong the network lifetime. Most existing works that focus on the lifetime optimization for data aggregation do not take the link quality into consideration. In this paper, we study the problem of Maximizing Reliability of Lifetime Constrained data aggregation trees (MRLC) in WSNs. Considering the NP-completeness of the MRLC problem, we propose an algorithm, namely Iterative Relaxation Algorithm (IRA), to iteratively relax the optimization program and to find the aggregation tree subject to the lifetime bound with a sub-optimal cost. To adapt to the distributed nature of the WSNs in practice, we further propose a Prufer code based distributed updating protocol. Through extensive simulations, we demonstrate that IRA outperforms the best known related work in term of reliability.

Echo-Aided Bat Algorithm is proved a good evolutionary computing to solve continuous problems in previous investigate. In this study, EABA is applied to solve the discrete problem that construct a network topology with spanning tree in wireless sensor networks (WSNs). In this application, the presentation of bat and design of fitness function perhaps affect the evolutionary results. For the demonstration of simulated results, EABA still presents a satisfied performance in some scenarios designed in this study. In addition, the constructed network topology of spanning tree based on global optimum solution found by EABA is used to estimate the network lifetime. Overall, this framework including network topology constructed by EABD and network lifetime estimated by transmission simulation is created in this study to aid the plan for duration of WSN deployment.

One ultimate goal of wireless sensor networks is to collect the sensed data from a set of sensors and transmit them to some sink node via a data gathering tree. In this work, we are interested in data aggregation, where the sink node wants to know the value for a certain function of all sensed data, such as minimum, maximum, average, and summation. Given a data aggregation tree, sensors receive messages from children periodically, merge them with its own packet, and send the new packet to its parent. The problem of finding an aggregation tree with the maximum lifetime has been proved to be NP-hard and can be generalized to finding a spanning tree with the minimum maximum vertex load, where the load of a vertex is a nondecreasing function of its degree in the tree. Although there is a rich body of research in those problems, they either fail to meet a theoretical bound or need high running time. In this paper, we develop a novel algorithm with provable performance bounds for the generalized problem. We show that the running time of our algorithm is in the order of O(mnα(m, n)), where m is the number of edges, n is the number of sensors, and α is the inverse Ackerman function. Though our work is motivated by applications in sensor networks, the proposed algorithm is general enough to handle a wide range of degree-oriented spanning tree problems, including bounded degree spanning tree problem and minimum degree spanning tree problem. When applied to these problems, it incurs a lower computational cost in comparison to existing methods. Simulation results validate our theoretical analysis.

In this paper we consider a problem of building a forwarding tree for multicast and convergecast traffic in short-range wireless sensor networks. Interference awareness and energy efficiency are the major design objectives for WSN protocols in order to maximize the network lifetime. The existing multicast algorithms aim at constructing low-energy cost trees. Adding interference-awareness, however, leads to increased throughput and further reduces the energy consumption by avoiding unnecessary retransmissions due to interference-induced packet losses. We propose a Localized Area-Spanning Tree (LAST) protocol for wireless short-range sensor networks. Unlike previous similar protocols, the LAST protocol reaches all the nodes in a given geographical area, rather than only specific individual nodes. When creating the tree, the protocol jointly optimizes the energy cost and the interference imposed by the structure.

Data aggregation in wireless sensor networks using ant colony algorithm

Routing algorithms for large-scale sensor networks should be capable of finding energy efficient paths to prolong the lifetime of the networks in a decentralized manner. With this respect, Ant System has several proper characteristics for routing algorithm in large-scale wireless sensor networks. First, its distributed mechanism enables routing algorithm to find a solution with only local information and be robust for uncertainties in wireless sensor networks. Second, the framework of the Ant System is proper to solve dynamic problems such as routing problem. Transition probability in Ant System can be used to estimate how good a given routing path is. Capturing these features, this work proposes two Ant Systems based routing algorithms, which are AS-RWSNs (Ant System for Routing in Wireless Sensor Networks) and SAAS-RWSN (Structure-Aware AS-RWSN). The AS-RWSN applies the original Ant System to routing algorithm for wireless sensor network and SAAS-RSN upgrades AS-RWSN with considering properties of network structure such as degree of node. In SAAS-RSN, sensors with high node degree have high data traffic since they have more routing paths. Consequently, SAAS-RSN achieves an energy balance over sensor network through this routing scheme. We demonstrate the effectiveness of the proposed algorithms by comparing three existing routing algorithms.

Data aggregation has been widely recognized as an efficient method to reduce energy consumption in wireless sensor networks, which can support a wide range of applications such as monitoring temperature, humidity, level, speed etc. The data sampled by the same kind of sensors have much redundancy since the sensor nodes are usually quite dense in wireless sensor networks. To make data aggregation more efficient, the packets with the same attribute, defined as the identifier of different data sampled by different sensors such as temperature sensors, humidity sensors, etc., should be gathered together. However, to the best of our knowledge, present data aggregation mechanisms did not take packet attribute into consideration. In this paper, we take the lead in introducing packet attribute into data aggregation and propose an Attribute-aware Data Aggregation mechanism using Dynamic Routing (ADADR) which can make packets with the same attribute convergent as much as possible and therefore improve the efficiency of data aggregation. This goal cannot be achieved by present static routing schemes employed in most of data aggregation mechanisms since they construct routes before transmitting the sampled data and thus can not dynamically forward packets in response to the variation of packets at intermediate nodes. Hence, we present a potential-based dynamic routing scheme which employs the concept of potential in physics and pheromone in ant colony to achieve our goal. The results of simulations in series of scenarios show that ADADR indeed conserve energy by reducing the average number of transmissions each packet needs to reach the sink and is scalable with regard to the network size.

Fault diagnosis based on extremely randomized trees in wireless sensor networks

Applying multimedia to Wireless Sensor Network (WSN) adds more challenges due to WSN resource constraints and the strict Quality of Service (QoS) requirements for multimedia transmission. Different multimedia applications may have different QoS requirements, so routing protocols designed for Wireless Multimedia Sensor Network (WMSN) should be conversant of these requirements and challenges in order to ensure the efficient use of resources to transfer multimedia packets in an utmost manner. The majority of solutions proposed for WMSN depends on traditional layered based mechanisms which are inefficient for multimedia transmission. In this paper we propose a cross-layer Ant based Routing Protocol for WMSN (CARPM) by using modified ant colony optimization (ACO) technique to enhance the routing efficiency. The proposed protocol uses an improved ACO to search for the best path that are satisfied with the multimedia traffic requirements. While making best decision the weightage is given to energy consumption, and queuing delay. The proposed cross layer scheme works between the routing, MAC, and physical layers. Since, the remaining power and timestamp metrics are exchanged from physical layer to network layer. Dynamics duty cycle assignment is proposed at MAC layer which changes according to traffic rate. The presented algorithm is simulated using NS2 and is proven to satisfy its goals through a series of simulations.

Wireless Sensor Network (WSN) has been widely implemented in large sectors such as military, habitat, business, industrial, health and environment. WSN is part of a distributed system where elements such as routing, load balancing, energy efficiency, node localization, time synchronization, data aggregation and security need to be addressed to improve its efficiency, robustness, extendibility, applicability and reliability. Despite multiple approaches proposed to improve all these aspects, there is still room for improvement in order to enhance the capability of WSN in terms of routing and energy efficiency. Ant Colony Optimization (ACO) is one of the approaches used to extend WSN capabilities because its heuristic nature is very suitable with distributed and dynamic environments. This study covers the common WSN aspects and performance evaluation criteria in addition to the list of previous studies that have used ACO approaches in WSN.

Wireless sensor networks (WSNs), often composed of a large number of sensor nodes with limited power, have been widely used for environmental monitoring and battlefield surveillance. A basic operation in such networks is data gathering. In the applications of data gathering without aggregation, the 1-hop nodes always incur much heavier traffic load compared with other nodes, which determine the lifetime of the whole network. Due to the energy constrained nature of sensor devices, energy-efficient methods should be employed for data gathering. In this paper, we propose a Load-Balanced and energy-efficient Tree (LBT) algorithm to maximize the lifetime of WSNs, which takes into account the load balance and energy efficiency of 1-hop nodes. To the best of our knowledge, we are the first to present the upper bound of network lifetime for data gathering without aggregation with tree-based topology. Simulation results demonstrate that our algorithm utilizes up to 98 % of the total energy of the 1-hop nodes and outperforms the state-of-the-art algorithms in terms of network lifetime. Furthermore, LBT can achieve a lifetime consistently close to the upper bound.

Wireless sensor networks (WSNs) have several special characteristics such as short transmission range and limited energy. The recent interest in sensor networks has led to a number of routing schemes that use the limited resources available at each sensor nodes more efficiently. In this paper a routing scheme based on ant colony algorithm (ACA), a novel approach to adaptive learning routing is proposed which is inspired by ants bypassing obstacle based on observations on real ants searching for food. The routing scheme concurrently considers the path energy cost and remainder of node along the path and tries finding the tradeoff between them. Also the routing scheme is compared with the directed diffusion (DD) routing. Simulation results show that the routing based on ACA has superior performance under all the experimental conditions with respect to the diffusion routing.

Disseminating data generated by sensors to sinks at different locations is one of essential functions in wireless sensor networks (WSNs). Recent research focuses much on how a source node forwards sensing data directly to the sink. In this paper, we propose a novel dissemination scheme that obtains five-layer data aggregation by introducing aggregator layers between sensors and sinks. The five aggregation layers from bottom to top are raw data aggregation, in-node data aggregation, group aggregation, aggregator aggregation and agent aggregation layers. In addition, the proposed network architecture for data delivery comprises two different transfer tiers. The lower tier is WSN and the upper tier is WLAN. The simulation results show that our scheme provides excellent throughput and reduces more power consumption for WSNs.

A wireless sensor network (WSN) consists of low power, low cost, limited memory and small in size sensor nodes, organise them in a cooperative network and perform three basic operations - sensing data from environment, computation, and data routing. Routing in WSN mainly focuses on data dissemination, data aggregation, life time of the network and limited bandwidth constraints in order to facilitate the efficient working of the network. Due to the limited battery power, the energy conservation is a critical aspect to design an efficient routing protocol in WSN. This paper proposes the energy efficient dynamic and self-optimised routing to prolong the life time of the network, QoS and solve the stagnation problem in the network.