Terms Of Network Lifetime Research Articles

An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks

In this paper, an improved version of the energy aware distributed unequal clustering protocol (EADUC) is projected. The EADUC protocol is commonly used for solving energy hole problem in multi-hop wireless sensor networks. In the EADUC, location of base station and residual energy are given importance as clustering parameters. Based on these parameters, different competition radii are assigned to nodes. Herein, a new approach has been proposed to improve the working of EADUC, by electing cluster heads considering number of nodes in the neighborhood in addition to the above two parameters. The inclusion of the neighborhood information for computation of the competition radii provides better balancing of energy in comparison with the existing approach. Furthermore, for the selection of next hop node, the relay metric is defined directly in terms of energy expense instead of only the distance information used in the EADUC and the data transmission phase has been extended in every round by performing the data collection number of times through use of major slots and mini-slots. The methodology used is of retaining the same clusters for a few rounds and is effective in reducing the clustering overhead. The performance of the proposed protocol has been evaluated under three different scenarios and compared with existing protocols through simulations. The results show that the proposed scheme outperforms the existing protocols in terms of network lifetime in all the scenarios.

A Two-Tier Adaptive Data Aggregation Approach for M2M Group-Communication

Network lifetime is the time interval in which the nodes are operational. Considering that machine-to-machine (M2M) devices have limited energy resources, an important challenge in M2M communications is to prolong the network lifetime. The constrained application protocol (CoAP) supports multi-target monitoring applications in M2M communications, allowing the creation and maintenance of groups, as well as their periodic communication. It is essential to aggregate the CoAP group-communication over the paths to increase the network lifetime of low-power M2M devices, since data aggregation reduces the use of energy-consuming hardware (e.g., central processing unit and wireless interface). However, the current data aggregation solutions do not specify how to support data aggregation with multiple CoAP-based groups in multi-target monitoring applications. In this paper, the proposed approach, called two-tier aggregation for multi-target applications (TTAMAs), aggregates the data originated from nodes belonging to either the same or different CoAP groups. Furthermore, TTAMA is an adaptive solution because it performs the data aggregation in accordance with the CoAP configurations, such as communication periodicity and data aggregation functions. We compare TTAMA with current data aggregation approaches that use minimum spanning tree and shortest path tree. The results show that TTAMA outperforms the related works in terms of network lifetime and energy consumption.

Performance Evaluation with Energy Consumption, Cluster Throughput and Packet Delivery Ratio of S-MAC Protocol in Wireless Sensor Network

Wireless sensor network are battery operated, and hence increasing the network lifetime is one of the primary concerns. This paper introduces energy efficient Sensor-Medium Access Control (S-MAC) protocol used in sensor network. Energy consumption is the main problem in wireless sensor network. So decrease the energy consumption and increase the network lifetime of sensor nodes in sensor networks using by S-MAC protocol. S-MAC protocol uses techniques for reduce energy consumption and also support self-configuration. The first, neighboring nodes are synchronized and go to sleep periodically. Second, the synchronized neighboring nodes make a virtual cluster to synchronize their listen and sleep periods, so the control packet overhead is kept low. Third, message passing is used to decrease latency and control overhead. In present work cluster is formed then cluster head is selected, and cluster head is fixed. S-MAC protocol was simulated in NS-2. To study the performance of S-MAC in terms of network lifetime, cluster throughput, packet delivery ration, total power and energy consumption for cluster head.

An Interference Aware Heuristic Routing Protocol for Wireless Home Automation Networks

Wireless Home Automation Networks consist of battery powered sensors and actuators that communicate with each other over wireless channels. The sensor nodes collect environmental information such as temperature, light intensity, humidity, and pressure to provide context-aware services and to facilitate smart home control. However, resource limitations, unpredictable topology changes, and interference introduce a number of challenges to the design of home automation protocols. One of the challenging tasks is developing energy efficient routing protocols to prolong the network lifetime. This paper proposes an interference aware heuristic routing protocol which determines the forwarding path between sensors and the base station using a heuristic function and a heuristic search algorithm. On the basis of local and global distance, longevity factor (LF), and link quality (LQ), the heuristic function generates a heuristic value for each node and this value is used in A_ search algorithm to determine the efficient route. Simulation results show that the proposed routing scheme outperforms GAHR and AODVjr protocols in terms of network lifetime, energy consumption, and message throughput. Furthermore, it achieves up to 15% increase in packet delivery ratio over GAHR protocol in a noisy environment

Lifetime Maximization of wireless sensor networks with multiple sinks using multiple paths and variable communication range

Maximising network lifetime in a wireless sensor network (WSN) used for maintaining crucial events and parameters is an important research area. In this paper, we define the lifetime of a network as the number of messages it can transfer to the sink node. We consider multiple sinks and propose three different variants of the algorithm to enhance the network lifetime in terms of number of messages successfully transmitted to any of the sinks. The first algorithm constructs tree with sink node as the root to every other node and the nodes choose the sink based on the shortest path. Sink shifting happens based on the predefined shift rate. In the second approach, we try to find an alternate path to reach the same sink before finally turning to another sink. In the third method, we increase the communication range in stages such that, it can avoid crucial nodes and reach the sink node by spending more energy. The performance comparison is done and shown that the network lifetime extended with the help of second and third approach by 8.75% and 33.42% than cluster based algorithm for sink selection (CASS). Alternate path with variable communication range has improved the network lifetime by 22.90% over alternate path approach.

EDAC: A Novel Energy-Aware Clustering Algorithm for Wireless Sensor Networks

Clustering is a useful technique for reducing energy consumption in wireless sensor networks (WSN). To achieve a better network lifetime performance, different clustering algorithms use various parameters for cluster head (CH) selection. For example, the sensor's own residual energy as well as the network's total residual energy are used. In this paper, we propose an energy-distance aware clustering (EDAC) algorithm that incorporates both the residual energy levels of sensors within a cluster radius as well as the distances. To achieve this, we define a metric that is calculated at each sensor based on local information within its neighborhood. This metric is incorporated within the CH selection probability. Using this metric, one can choose the sensors with low residual energy levels to have the greatest impact on CH selection which results in CH selection being biased to be close to these sensors. This results in reducing their communication energy cost to the CH. Simulation results indicate that our proposed EDAC algorithm outperforms both the LEACH and the energy-efficient DEEC protocols in terms of network lifetime.

NetBAN, a concept of Network of BANs for Cooperative Communication: energy awareness routing solution

In this paper, a NetBAN which is a concept of network of body area networks (BANs) or wireless body area networks (WBANs) is introduced and a routing solution intending to help a group of WBANs to cooperate for relaying packets according to the energy consumption rate and the communication link quality is proposed. The main goal is to provide to the sensors a technique that helps them deliver their data even when the coordinator's battery is very low or empty or else the connection to the access point is lost, what leads to balancing energy consumption between cooperating coordinators. For this purpose, an energy threshold-based technique is used and energy-aware optimised link state routing (EA-OLSR) is defined and used. Simulation results show interesting performances in terms of network lifetime with a gain of about 30% and data delivery about 20%.

Clustering algorithm for wireless sensor networks : the honeybee swarms nest-sites selection process based approach

A cluster-based sensor network with data aggregation on cluster heads is the most popular approach for optimising the energy consumption, in order to maximise the overall network lifetime. Clustering is also used for optimising the quality of service and scalability in sensor networks. In large-scale networks, the management of nodes becomes a challenge. It is therefore necessary that, these sensors act in a self-organised manner to perform tasks. A number of protocols has been proposed. Swarm intelligence based models, inspired by social insects behaviours, provide the most powerful tools that lead to a global intelligence through simple actions in a self-organised manner. In this paper, we proposed a distributed clustering approach called NEST, based on the nest-sites selection process of a honeybee. Extensive experiments have been conducted and the results demonstrated that our algorithm delivers better performance in terms of network lifetime, delivered packets, end-to-end delay, energy consumption and efficiency.

무선센서네트워크에서의 위치기반 클러스터 구성을 통한 효율적인 라우팅 방안 연구

Maintaining efficient energy consumption and elongating network lifetime are the key issues in wireless sensor networks. Existing routing protocols usually select the cluster heads based on the proximity to the sensor nodes. In this case the cluster heads can be placed farther to the base station, than the distance between the sensor nodes and the base station, which yields inefficient energy consumption. In this work we propose a novel algorithm that select the nodes in a cluster and the cluster heads based on the locations of related nodes. We verify that the proposed algorithm gives better performance in terms of network life time than existing solutions.

Energy-Efficient Dynamic Packet Downloading for Medical IoT Platforms

This paper proposes a polynomial-time algorithm for energy-efficient dynamic packet downloading from medical cloud storage to medical Internet-of-Things (IoT) devices. The medical cloud can distribute its own medical data to medical IoT devices via access points. Therefore, network disconnection can happen between the medical cloud and medical IoT devices when power/energy management in each access point is not efficient. This situation is especially harmful in in-hospital network architectures, because the architecture usually has strict requirements in terms of reliability. Therefore, this paper proposes a dynamic energy-efficient algorithm, which computes the amount of power allocation in each access point based on the buffer backlog size and channel states under the consideration of buffer stability. With the proposed adaptive algorithm, each access point calibrates its own parameters for more adaptive power/energy management. The performance of the proposed algorithm is evaluated in terms of network lifetime, and it is observed that the proposed algorithm achieves the desired performance.

Cognitive Power Management in Wireless Sensor Networks

Dynamic power management (DPM) in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node’s operating mode by dynamically toggling the on/off status of its units based on predictions of event occurrences. However, since each mode change induces some overhead in its own right, guaranteeing DPM’s efficiency is no mean feat in environments exhibiting non-determinism and uncertainty with unknown statistics. Our solution suite in this paper, collectively referred to as cognitive power management (CPM), is a principled attempt toward enabling DPM in statistically unknown settings and gives two different analytical guarantees. Our first design is based on learning automata and guarantees better-than-pure-chance DPM in the face of non-stationary event processes. Our second solution caters for an even more general setting in which event occurrences may take on an adversarial character. In this case, we formulate the interaction of an individual mote with its environment in terms of a repeated zero-sum game in which the node relies on a no-external-regret procedure to learn its mini-max strategies in an online fashion. We conduct numerical experiments to measure the performance of our schemes in terms of network lifetime and event loss percentage.

Switching Algorithm with Prediction Strategy for Maximizing Lifetime in Wireless Sensor Network

In wireless sensor networks (WSNs), the sensed data of each node are usually gathered through a data collection tree rooted at the sink node. The data collection tree generated randomly usually does not have the longest network lifetime. How to prolong the network lifetime is one of the main challenges in WSNs. In this paper, we propose a switching algorithm with prediction strategy (SAPS) to enhance the lifetime of WSNs through reducing the load of the node with the highest load by switching its descendants. In SAPS, the shortest path to the sink is chosen for each switched node to ensure that the routing tree is shortest, thus reducing the delay and energy expenditure of data collection. Furthermore, a prediction strategy which ensures that the highest load in the network decreases in each switching is developed to guarantee high efficiency and fast convergence of the algorithm. A distributed version of our algorithm, called DSAPS, is also designed. Simulation results demonstrate that our algorithms outperform existing methods in terms of network lifetime, maximum level of the routing tree, energy expenditure of switching, energy expenditure of data collection in each round, and rate of convergence.

Data gathering in delay tolerant wireless sensor networks using a ferry.

In delay tolerant WSNs mobile ferries can be used for collecting data from sensor nodes, especially in large-scale networks. Unlike data collection via multi-hop forwarding among the nodes, ferries travel across the sensing field and collect data from sensors. The advantage of using a ferry-based approach is that, it eliminates the need for multi-hop forwarding of data, and as a result energy consumption at the nodes is significantly reduced. However, this increases data delivery latency and as such might not be suitable for all applications. In this paper an efficient data collection algorithm using a ferry node is proposed while considering the overall ferry roundtrip travel time and the overall consumed energy in the network. To minimize the overall roundtrip travel time, we divided the sensing field area into virtual grids based on the assumed sensing range and assigned a checkpoint in each one. A Genetic Algorithm with weight metrics to solve the Travel Sales Man Problem (TSP) and decide on an optimum path for the ferry to collect data is then used. We utilized our previously published node ranking clustering algorithm (NRCA) in each virtual grid and in choosing the location for placing the ferry’s checkpoints. In NRCA the decision of selecting cluster heads is based on their residual energy and their distance from their associated checkpoint which acts as a temporary sink. We simulated the proposed algorithm in MATLAB and showed its performance in terms of the network lifetime, total energy consumption and the total travel time. Moreover, we showed through simulation that nonlinear trajectory achieves a better optimization in term of network lifetime, overall energy consumed and the roundtrip travel time of the ferry compared to linear predetermined trajectory. In additional to that, we compared the performance of your algorithm to other recent algorithms in terms of the network lifetime using same and different initial energy values.

A Multi-Chain Based Hierarchical Topology Control Algorithm for Wireless Sensor Networks

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

Betweenness centrality based connectivity aware routing algorithm for prolonging network lifetime in wireless sensor networks

Network lifetime is the key design parameter for wireless sensor network protocols. In recent years, based on energy efficient routing techniques numerous methods have been proposed for enhancing network lifetime. These methods have mainly considered residual energy, number of hops and communication cost as route selection metrics. This paper introduces a method for further improvement in the network lifetime by considering network connectivity along with energy efficiency for the selection of data transmission routes. The network lifetime is enhanced by preserving highly connected nodes at initial rounds of data communication to ensure network connectivity during later rounds. Bassed on the above mentioned concept, a connectivity aware routing algorithm: CARA has been proposed. In the proposed algorithm, connectivity factor of a node is calculated on the basis of Betweenness centrality of a node and energy efficient routes are found by using fuzzy logic and ant colony optimization. The simulation results show that the proposed algorithm CARA performs better than other related state-of-the-art energy efficient routing algorithms viz. FML, EEABR and FACOR in terms of network lifetime, connectivity, energy dissipation, load balancing and packet delivery ratio.

An Energy-Aware Cross-Layer Cooperative MAC Protocol for Wireless Ad Hoc Networks

Cooperative communication (CC) has recently emerged as an effective technique to combat the channel impairment, energy limitation and radio spectrum constraints. Physical-layer Network Coding (PNC) is an alternative applied in wireless networks to reduce transmission time slots and deliver higher throughput while also being energy-efficient. In order to benefits from both CC and PNC characteristics an efficient Medium Access Control (MAC) protocol is required. This study introduces a new cooperative MAC protocol called EAP-CMAC (Energy Aware Physical-layer Network Coding Cooperative MAC) that integrates cooperative communication into PNC in wireless ad-hoc networks. In EAP-CMAC, the best transmission mode is selected among direct transmission, traditional cooperation and PNC-based transmission by considering the destination queue and source-destination link quality. Moreover, a joint relay selection and power allocation algorithm is proposed based on location information and the nodes residual energy that significantly improves the network lifetime and energy saving in wireless networks. The simulation results indicate that EAP-CMAC outperforms IEEE 802.11 and CoopMAC in terms of network lifetime by 50% and 140% respectively. Furthermore, the proposed optimal power allocation enhances EAP-CMAC performance in terms of network lifetime by 7% compared to equal power allocation.

A Refined Integrated MAC and Routing Protocol with Quantification Algorithm to Mitigate Hotspot Problems in Wireless Sensor Networks

Background: Wireless Sensor Networks (WSN) is an interconnected connection of two or more sensor nodes. A typical sensor node can perform Sensing, Computing and Communication. Objective: The core objective of this paper is to mitigate or to reduce the impact of the Hotspot effect in Wireless Sensor Network (WSN) by using a refined integrated MAC and Routing protocol and a quantification algorithm. Methods/Analysis: We are using a refined integrated MAC and routing protocol which divides the network into tiers. We also propose a quantification algorithm, which decides the optimum number of nodes in each tier to mitigate the hot-spot problem. The work is simulated in NS2. Findings: We simulated our work in NS2 and found that the proposed quantification algorithm along with Refined Integrated MAC and Routing Protocol outperforms SMAC in terms of network lifetime. Conclusion: The proposed protocol along with quantification algorithm increases the network life time and reduces the impact of the hotspot effect when compared with conventional protocols.

A Hybrid Algorithm for Preserving Energy and Delay Routing in Mobile Ad-Hoc Networks

The Quality of Service (QoS) routing protocol plays a vital role in enabling a mobile network to interconnect wired networks with the QoS support. It has become quite a challenge in mobile networks, like mobile ad-hoc networks, to identify a path that fulfils the QoS requirements, regarding their topology and applications. The QoS routing feature can also function in a stand-alone multi hop mobile network for real-time applications. The chief aim of the QoS aware protocol is to find a route from the source to the destination that fulfils the QoS requirements. In this paper we present a new energy and delay aware routing method which combines Cellular automata (CA) with the Genetic algorithm (GA). Here, two QoS parameters are used for routing; energy and delay. The routing algorithm based on CA is used to identify a set of routes that can fulfill the delay constraints and then select a reasonably good one using GAs. The results of Simulation show that the method proposed produces a higher degree of performance than the AODV and another QoS method in terms of network lifetime and end-to-end delay.

Efficient Overlay Construction for Wireless Sensor Networks

In this paper, we propose a new algorithm for efficient overlay construction for wireless sensor networks to minimize energy consumption thereby enhancing the network lifetime. In the proposed algorithm, sensor nodes are grouped into clusters of unequal size and the selection of cluster heads (CHs) depends on their residual energy. To route the data to the sink, a routing overlay (RO) of the CHs is constructed and this is done only once during the lifetime of the network. We devise an efficient data relaying strategy to balance the energy consumption of the CHs in the RO. The proposed algorithm also replaces a CH and reconfigures the RO by making decision locally. We perform extensive experiments through simulation run. The simulation results are compared with the existing algorithms which show that the proposed algorithm outperforms in terms of network lifetime, energy consumption and other performance metrics.

Enhancing the Performance of Leach Protocol in Wireless Sensor Network

is tremendous increase in popularity of WSNs as the sensor network connects the virtual world and physical world together. Sensors nodes can be deployed in hostile environment where there is no access of human beings. Sensor nodes rely on battery power where it becomes a difficult task to replace the battery. So to improve the networks energy is very important task. To overcome this problem, a routing protocol was proposed known as Low-Energy Adaptive Clustering Hierarchy (LEACH). The implementation of the protocol is done using MATLAB 2013. In this thesis we proposed a new modified LEACH algorithm, in which to calculate the threshold value for next round we consider the remaining nodes energy of the network. A comparison between Leach, Leach-SCH and proposed Leach is done on the basis of the network lifetime. From the comparative study, we can conclude that the new proposed algorithm is better than Leach and Leach-SCH in terms of network lifetime.