A Coverage-Based Scheduling Algorithm for WSNs

Wireless Sensor Networks (WSNs) consist of a large number of small and low cost sensor nodes powered by small batteries and equipped with various sensing devices. Usually, for many applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected to gather the required data for quite some time, say for years. Since each sensor node has limited energy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i) random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always be routed from source to sink. In this paper, we propose a novel approach for sleep scheduling of sensor nodes using a tree and an energy aware routing protocol which is integrated with the proposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of the tree remain awake and the leaf nodes are made to sleep. This provides an assured path from any node to the sink node. The tree is periodically reconstructed considering the remaining energy of each node with a view to balance energy consumption of nodes, and remove any failed nodes from the tree. The proposed approach also considerably reduces average energy consumption rate of each node as we are able to put more number of nodes to sleep in comparison to other approaches. Additional fault-tolerance is provided by keeping two paths from each node towards the sink. Extensive simulation studies of the proposed routing protocol has been carried out using Castalia simulator, and its performance has been compared with that of a routing protocol, called GSP, which incorporates sleep scheduling using random approach. The simulation results show that the proposed approach has longer network lifetime in comparison to that provided by GSP, and the energy consumption of nodes is also balanced.

Wireless networks play a crucial role in the communication systems nowadays. Wireless networks are being increasingly used in the communication among devices of the most varied types and sizes. User mobility, affordability, flexibility and ease of use are few of many reasons for making them very appealing to new applications and more users everyday. A Wireless Sensor Network (WSN) is composed of sensor nodes spread over the field to sense the data. The sensed data must be gathered & transmitted to Base Station (BS) for end user queries. The used sensor nodes being in- expensive having low computation power & limited energy so are not as much reliable as their expensive macro sensor counter parts but their size and cost enable hundred to thousand of micro sensors to achieve high quality fault tolerant system. In an environment where in each round all sensor nodes have to send data to base station; it is required to effectively utilize energy of sensor nodes so as to increase the life- time of the system. The use of data aggregation & fusion as proposed in LEACH increases system lifetime by a factor of 8 as compared to conventional routing protocols. In this work, our main focus is the static sensors are randomly selected and the base stations have their information all a priori. Basically, the sensors are in direct communication range of each other and can transmit to and receive from the base station. The nodes periodically sense the environment and have always data to send in each round of communication. The nodes fuse/ aggregate the data they receive from the others with their own data, and produce only one packet regardless of how many packets they receive. The problem is to find a routing scheme or an efficient protocol to deliver data packets collected from sensor nodes to the base station. It maximizes the lifetime of the sensor network under the system model given above. However, the definition of quality of service of the sensor network provides is not specified. Secondly, where the nodes are densely deployed, the quality of the system is affected as soon as a significant amount of nodes die, since adjacent nodes record identical or related data. In this case, the lifetime of the network is the time elapsed until half of the nodes or some specified portion of the nodes die. In general terms, the time in rounds where the last node depletes all of its energy defines the lifetime of the overall sensor network. Taking these different possible requirements under consideration, our work provides a proper timing of all deaths for all algorithms in detail as well as chooses the shortest possible path for communication with better memory management scheme and leaves the decision which one to choose to system designers.

Scheduling sensor activities is an effective way to prolong the lifetime of wireless sensor networks (WSNs). In this paper, we explore the problem of wake-up scheduling in WSNs where sensors have different lifetime. A novel local wake-up scheduling (LWS) strategy is proposed to prolong the network lifetime with full coverage constraint. In the LWS strategy, sensors are divided into a first layer set and a successor set. The first layer set which satisfies the coverage constraint is activated at the beginning. Once an active sensor runs out of energy, some sensors in the successor set will be activated to satisfy the coverage constraint. Based on the LWS strategy, this paper presents an ant colony optimization based method, namely mc-ACO, to maximize the network lifetime. The mc-ACO is validated by performing simulations on WSNs with different characteristics. A recently published genetic algorithm based wake-up scheduling method and a greedy based method are used for comparison. Simulation results reveal that mc-ACO yields better performance than the two algorithms.

A large number of sensor nodes are deployed to remote locations and left unattended for a long time in wireless sensor network applications. When a battery-powered sensor node depletes its energy, it is assumed as “dead” and recharging or replacing the battery is not possible in most of the applications. Lifetime of the wireless sensor network depends on the efficient use of available restricted energy. Railway monitoring application of Linear Wireless Sensor Networks (LWSNs) which are a subclass of wireless sensor networks is considered in this paper. The objective of this study is to present the effect of proper node deployment in extending the linear wireless sensor network lifetime. Thanks to proposed deployment scheme, it is shown that the energy consumption of the LWSN is lowered and thus the lifetime of the network is increased.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

We consider the problem of scheduling in wireless sensor networks for the purposes of aggregation convergecast. We observe that existing schemes adopt essentially a two phase approach, consisting of, first, a tree construction and, second, a scheduling phase. Following a similar approach, we propose two new improvements, one to each of the two phases. Starting with a new lower bound on the schedule length, we make use of it in the tree construction phase. The tree construction phase consists of solutions to instances of bipartite graph semi-matchings. The scheduling phase is a weight-based priority scheme that obeys dependency (tree) and interference constraints. Our extensive experiments show that, overall, our proposed solution not only outperforms all previously proposed solutions in terms of schedule length, but it also significantly extends the network's lifetime.

Maximization of lifetime of wireless sensor network (WSN) is an emerging area of research in present scenario. Many authors are performing their research work, so that they could achieve lower energy consumption for the sensor network which leads to increase in lifetime of network. Our work focuses on sink mobility in a fixed trajectory within a wireless sensor network while sensed data are required to be collected. We divide the whole sensor network into two different regions as direct communication area (DCA) and multi-hop communication area (MCA). Sensors node that lies in DCA is at one hop count distance from the sink node trajectory while sensors within MCA are at more than one hop count from the trajectory. We considered all the sensors that are within DCA as subsink nodes. During sink mobility, whenever a subsink is closer to the mobile sink node, then it starts transmitting its data to the sink node. But those sensors that are within MCA needs to search an appropriate sink node for sending its sensed data to the subsink so that on further stage, that subsink could provide those data to the sink node whenever it is in nearest proximity of that subsink. Basically, a sink node is the ultimate destination for the data while a subsink node acts as a relay node for the nodes that are within MCA. So our work is to find out the appropriate subsink node from a given set of subsinks. For doing so, we used location-aided routing on global positioning system (GPS)-enabled sensors and sink node. Our work is validated through simulation experiments using NS-2.

Energy-efficient coverage protocol based on stable and predictive scheduling in wireless sensor networks

Wireless sensor networks are the set of nodes with cooperative nature with the purpose of sensing and monitoring. Every node comprises with the sensing, computing, broadcasting, processing capacity, energy utilization and actuation. As the sensors are communicate through wireless medium the self-organizing capacity being utilized handle numerous amounts of sensor nodes spread over a huge geographic section for a large-scale environment observation. To attain an enhanced coverage, more sensors have to be active, then more energy would be utilized and the network lifetime is reduced. In wireless sensor network, the coverages and life time are significant and basic concern regarding the performance of the network.. A method of improving the coverage and network lifetime of a cooperative sensor network is proposed. Nearest Neighbor Assertion (NNA) method determines the nearest nodes which are spatially and temporally collided and interference with each other. To get better the search time, employ an n-d tree data structure, data driven binary search tree. A neuro-fuzzy based decision making id done regarding the scheduling of sensors in various modes.

Wireless Sensor Networks is dispersed by a group composed of sensors and Base Stations. It can be used in various applications of remote monitoring system. Sensor nodes route the collected data to the Base Station via multi-hop wireless links. These sensors typically use batteries to operate, the battery cannot be replaced when the depletion of energy resources. Therefore, how to use energy-saving sensor networks to extend the overall working time efficiently is an important subject. Our research is based on A Power Control Mechanism based on Sleep Scheduling for Wireless Sensor Networks. We proposed a refined mechanism of routing protocol for wireless sensor networks with sleep scheduling. In wireless sensor network with sleep scheduling, active node adjusts its working time and each step in sleeping state earlier. In the multi-hop transmission mode, each node broadcasts the packet to confirm the receiving node. Therefore, we use routing information to reduce the number of broadcasting during transmission. When route node with low rest power cannot transfer, in order to remain completed route, we can execute interrupt handler procedure to reduce the package loss. Finally, to achieve power efficiency, we will simulate if the proposed algorithm can reduce energy consumption effectively in the data transmission procedure.

In wireless sensor networks, sensor nodes have limited battery power. Data aggregation is an important technique in a wireless sensor network to reduce the energy consumption by eliminating the redundant data and delivering useful data to the user. Data aggregation technique is used to gather the data sensed by the sensor nodes in the network and aggregates the sensed data in an energy-efficient way so that overall network lifetime can be increased. Cluster, tree, chain, and grid are some of the architectures for data aggregation in wireless sensor networks. In this paper, authors present an analysis-based survey of data aggregation protocols for tree-based architecture in wireless sensor networks. The authors analyze each algorithm on the basis of performance measurements such as network lifetime, energy consumption, and node distance. Authors also compare these algorithms on the basis of the preferred parameter and a key feature of each algorithm. In the fifth section of the paper, authors described the proposed approach to construct the data aggregation tree to maximize the network lifetime. In the proposed approach, authors used distance parameter to construct minimum spanning tree, and other parameters such as load and energy are preferred in a balanced manner to reduce the energy consumption and to maximize the network lifetime.

Extensive research is being done on Wireless sensor Networks (WSNs) in present decade. WSNs consist of large number of sensor nodes which perform sensing of certain phenomena and send the sensed data to the sinks. This operation consumes energy of sensor nodes which effects the lifetime of a network. To prolong the lifetime of WSNs various strategies and routing algorithms have been proposed. Use of mobile sinks has proved effective in this respect. In this paper we are analyzing the impact of multiple mobile sinks with proactive hierarchical clustering protocols LEACH and network reactive hierarchical protocol TEEN. This paper will give simulation based analysis of using multiple mobile sinks in network and their effect on lifetime of a network. Performance analysis will be done on basis of dead nodes, alive nodes, throughput and residual energy.

Clustering techniques in wireless sensor networks (WSNs) compare to random selection techniques is less costly due to the saving of time in journeys, reduction in number of transmissions and receptions at each node, identification, contacts, etc., which are valuable for increasing the overall network life, scalability of WSNs. Clustering sensor nodes is an effective and efficient technique for achieving the requirement. The maximizing lifetime of network by minimizing energy consumption poses a challenge in design of protocols. Therefore, proper organization of clustering and orientation of nodes within the cluster becomes one of the important issues to extend the lifetime of the whole sensor network through Cluster Head (CH). We investigate the problem of energy consumption in CH rotation in WSNs. In this paper, CH selection algorithm has been proposed from an unequal cluster. The total energy and expected number of packet retransmissions in delivering a packet from the sensor node to other nodes have been mathematically derived. In this paper, we applied the approach for producing energy-aware unequal clusters with optimal selection of CH and discussed several aspects of the network mathematically and statistically. The simulation results demonstrate that our approach of re-clustering in terms of energy consumption and lifetime parameters.

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

Congestion severely affects the performance of a wireless sensor network in two aspects: increased data loss and reduced lifetime. This paper addresses these problems by introducing a mobile sink based routing scheme for congestion avoidance and energy efficient routing in wireless sensor networks. The proposed scheme utilizes the sink mobility and an in-network storage model that is used to set up mini-sinks along the mobility trajectory of the sink. Mini-sinks are responsible for collecting data from the sensor nodes located in their vicinity, thus avoiding data flow to a single data collection point, e.g., a static sink that is the major cause of congestion, data loss and reduced lifetime of the sensor network. Also, in the proposed scheme data only has to travel a limited number of hops to reach the nearest mini-sink which helps to improve the energy consumption of the sensor nodes. Through simulation we show the effectiveness of the given routing scheme in terms of congestion avoidance and increased lifetime of the wireless sensor network.