Modeling and energy consumption evaluation of a stochastic wireless sensor network

Sensor nodes are small and low-cost portable devices that are connected wirelessly to form a wireless sensor network. Sensor nodes are typically powered by a chemical battery source that has a load-dependent finite lifetime. Most applications require wireless sensor networks to operate reliably for an extended period of time beginning with their deployment. To ensure both the longevity of a wireless sensor network via power management techniques and development of a self-powered sensor node, it is important to understand a sensor node’s operational energy consumption. It is well understood that wireless sensor network lifetime has a strong functional dependence on sensor node lifetime. This paper presents the development of a stochastic model to capture the expected energy consumption of a schedule-driven sensor node per cycle of operation by utilizing renewal theory, random stopping criteria, and Wald’s inequality. The model captures the expected energy consumed due to generic operation of a schedule-driven sensor node when an external event occurs (i.e., node level activities) and energy consumed due to carrier sense multiple access/collision avoidance medium access control protocol (i.e., retransmission attempts, channel listening, and other network level activities). The stochastic energy model is used to compute the expected lifetime and cycle lifetime of the sensor node. This paper also computes the deterministic energy bounds corresponding to the minimum and maximum energy consumption of a sensor node per cycle of operation. Analytical and numerical model validations are performed and presented.

Outlier detection plays a crucial role in secure monitoring in Wireless Sensor Networks (WSN). Moreover, outlier detection techniques in WSN face the problem of limited resources of transmission bandwidth, energy consumption and storage capacity. In this paper, similar flocking model is proposed and a cluster algorithm based on similar flocking model (CASFM) is put forward to detect outliers in real-time stream data collected by sensor nodes. The similar flocking model improves the Vicsek model by introducing the similarity between individuals and velocity updating rule, which causes similar objects to cluster quickly. In order to save energy, CASFM algorithm preprocesses similar data on the sending sensors first, which greatly reduces the transmission of similar data. So the communication overhead is decreased. With the characteristics of self-organization and fast convergence of flocking model, stream data can be clustered quickly. The experimental results show that the proposed algorithm can detect outliers effectively with less energy consumption.

This paper considers the design of wireless sensor networks in which a set of smart battery-powered sensor nodes cooperatively form an ad hoc communications network for monitoring and control applications. The paper examines ways of extending the life of such networks by introducing a 'sleep mode' in the sensor node. Quantitative analysis is used to show that although there is a complex relationship between 'sleeping' and energy conservation, it is possible to make significant energy savings while incurring only modest degradation in performance. An optimum energy saving curve is derived which provides a basis for the design of extended-life ad hoc wireless sensor networks.

A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. Active/Sleep operation modes have also been used to separately model and evaluate performance and availability of WSNs. The advancement in technology and continuous improvements of the existing protocols and application implementation demands continue to pose great challenges to the existing performance and availability models. In this study the need for integrating performance and availability studies of WSNs in the presence of both channel and node failures and repairs is investigated. A framework that outlines and characterizes key models required for integration of performance and availability of WSN is in turn outlined. Possible solution techniques for such models are also highlighted. Finally it is shown that the resulting models may be used to comparatively evaluate energy consumption of the existing motes and WSNs as well as deriving required performance measures.

The wireless sensor network (WSN) has been extensively used to monitor and control the natural ecosystem on a large scale like air quality, natural life, etc. Low battery power,low storage, and limited processing ability are the most critical areas of concern in WSN. To reduce energy utilization, the sensor nodes in WSN work in a cyclic process between active and sleep mode. A certain number of nodes are chosen active and they are responsible for sensing as well as data transmission and rest of the nodes are gone to sleep. In order to lengthen the lifetime of network, in this paper we proposed a level wise periodic tree construction algorithm that uses a specific set of nodes to participate in tree construction, instead of all the nodes, to minimize the energy consumption. In this proposed approach, the main idea is to put the nodes, which are currently active and have already spent a significant amount of energy, to sleep mode, while giving chances to the leaf nodes, which has comparatively spent less energy, to become an active node and maintain connectivity. The performance of the proposed protocol is evaluated using the Castalia simulator. The simulation results show that the proposed level-wise periodic tree construction approach increases the durability of the network in conjunction with the non-level approach.

The intensive traffic loads and high data rate in wireless sensor networks (WSNs) can cause congestion and have negative impact on the performance such as increased delay and energy consumption by sensor nodes. Moreover, the information provided by sensors may have different importance. The data packets which have more priority should reach sink nodes with reduced delay compared to low priority traffic. In this paper, we propose a delay-aware priority based routing scheme, called DAPR to alleviate congestion in wireless sensor networks. Our proposed mechanism uses queuing model at each sensor node which differentiates high-priority (HP) and low-priority (LP) data packets and transmits them in different way so that HP packets can be reached at sink nodes with reduced delay compared to LP packets. DAPR uses multipath routing technique which helps to alleviate congestion at certain places in the network, balances the load of traffic across several sensor nodes, and maximizes the network lifetime by reducing the energy consumption by sensor nodes. Simulation results show that our protocol achieves lower average end-to-end delay, more energy savings by sensor nodes, and less sensitive due to the impact of node failure than EQSR and MCMP protocols.

WITHDRAWN: Developing a software reliability evaluation model for wireless sensor networks based on analysis of software fault growth

One of the major challenge in Wireless Sensor Networks (WSN’s) deployment is efficient energy consumption. Critical distance, proper routing algorithm and error control coding techniques can be used for energy optimization. As WSN contains a large number of power constrained sensors, the sensed data from the environment should be transmitted in a cooperative way to the base station (BS). The pattern of the clustering structure can extend the sensor network life time, reduce the total consumed energy and regulate the data transmission. Clustering concept combines group of sensors which are located in the same communication range. Some of the routing protocol like, SEED, LEACH, SEP, Z-SEP etc., suffers from idle listening problem, which cannot cope with an environment with sensor nodes. It leads to energy wastage across the network. To manage energy efficiency and traffic heterogeneity issues, a new routing protocol called enhanced energy efficient sleep awake aware intelligent sensor network (EEESAA) is proposed. Here, one sensor in each group will be in active mode whereas other sensors entered in sleep mode. Based on the nodes energy, sleep and awake node pairs will be altered. In the proposed method, one slot is allotted for group of pairs. The proposed approach is evaluated and compared against LEACH, SEP and Z-SEP protocols. Simulation results show that EEESAA protocol performs better than LEACH, SEP, Z-SEP in terms of cluster head selection, throughput, number of alive & dead nodes and network lifetime.

Backgate biasing is a promising technique for highspeed systems. Leakage can be reduced during standby periods by reverse bias while adequate bias in active mode can balance process and temperature variations. This technique introduces no delay penalty in active mode but slow wake up time results in system performance degradation. In this paper, a backgate bias accelerator achieving 24ns/V sleep-to-active mode transition rate is demonstrated in a 90 nm CMOS technology. The circuit performs auto-calibration of the transition time as a function of the Sleep and Active mode backgate bias voltages. Those can therefore be tuned on-chip according to process variations and/or operating conditions. The accelerator occupies less than 2.5% of the total chip area, consumes 600μW during the transitions and doesn’t add any bias current during active and sleep modes.

Wireless sensor networks are set of thousands or more micro sensor nodes that one of the most important constraints of them is energy consumption of these sensor nodes .Since these nodes have very small dimensions, energy production needs batteries with limited power. It is obvious that the problem of energy reduction was always one of the biggest challenge in these networks. In these networks, routing is data-centric. On the other hand, in these networks it is only important to receive the data packet by the BS. In this paper we propose a new method for routing in wireless sensor networks that instead of using the traditional routing methods attempts to add nodes which have the minimum distances from each other. In our innovative method, we define node arrangement such that always data packets which are sent, arrive to destination through the shortest path which cause to reduce the total energy consumption. Since the sensor nodes which are near to each other have many redundant data, we can aggregate data packet continuously in the network. Simulation results show that our proposed algorithm works very well in spaces with large dimensions (size) and can reduce the total energy consumption more than the best traditional algorithms such as PEGASIS and leach with factor of 34%.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.

In recent development of vehicular adhoc network the consumption of energy by its nodes is major problem now a day. To overcome this problem many algorithms are proposed effectively by different researcher. The two main aspects that can resolve this issue is by having proper routing and network design. Many existing routing protocols are available with vehicular adhoc network, but only few of them can be utilize to resolve with the energy efficient problem. In wireless sensor network when the nodes are deployed they consumed most of the energy continuously to broadcast the message in multi hop connectivity. Generally nodes remain active even when there is no message to forward. This keeps decreasing the energy level of sink node. As a result the performance of the network gets dropped down. In our proposed algorithm, we aim to resolve this by relaying the node energy between active and passive mode. In our methodology sensor nodes gets triggered into active mode after a specific interval of time to exchange its data among them. The simulation results show that our proposed scheme, surpass from the other existing schemes. At the same time, each sensor node will restore its energy at regular interval as well as maintain high reception rate and low delay for multi-hop network.

The periodic data collection and energy consumption are the main issue for collision in wireless sensor networks, which generally rely on non-renewable energy sources. In recent days, the energy harvesting sources are based on solar, wind, and vibration for harvesting electric energy. The sensor nodes are unable to communicate with other nodes due to an unsteady supply of energy from energy harvesting sources, whereas a node cannot predict an energy level of nearer nodes that can receive a transmitted data packet from it. Sometimes the probability of losing or collision of data packets in the target node is more due to insufficient power supply. This proposed paper is designed to collect data by using protocols like probabilistic retransmission (PRT) and also probabilistic retransmission (PRT) with collision impact (PRT-CI), in addition to the supply of optimal power allocation source to sensor nodes which enhances the performance of the overall process. The number of data packets is retransmitted on the probability of reception using PRT as well as the collision impact (PRT-CI) evaluates the data packet with a response probability of each node.

Wireless sensor networks (WSNs) have attracted great attention because of their applicability in a variety of applications in day-to-day life such as structural monitoring, healthcare, surveillance, etc. Energy conservation is a challenging issue in the context of WSN as these networks are usually deployed in hazardous and remote applications where human intervention is not possible; hence, recharging or replacing the battery of sensor nodes is not feasible often. Apart from energy conservation, target coverage is also a major challenge. Scheduling the nodes to exist in active and sleep modes is an efficient mechanism to address the energy efficiency and coverage problem. The chapter proposes an ARIMA model-based energy consumption prediction approach such that the set cover scheduling may be optimized. The chapter compares the efficiency of several ARIMA-based models, and the results show that the ARIMA (0,1,2) model provides best results for the considered scenario in terms of energy consumption.