Conceptual Agent-Based Model for Optimal Power Utilization in Wireless Sensor Networks

Wireless sensor networks (WSN) have become a significant research challenge, attracting many researchers. This paper provides an overview of collaborative WSN, reviewing the algorithms, techniques and state-of-the-art developed so far. We discuss the research challenges and opportunities in this area. The major focus is given to cooperative signal and information processing in collaborative WSN in order to expose important constraints in wireless applications which require distributed computing, such as node localization, target detection and tracking. In this paper, we also present and discuss the applications of multi-agent systems into WSN as a core technology of cooperative information processing.

One of the main objectives of query processing in wireless sensor networks is to achieve high resource efficiency. In this paper, we focus on scheduling multiple queries which may have temporal and spatial overlapping in querying operations. Our purpose is to schedule the operations on the sensor nodes so as to save the total cost by maximizing the overlapping in time among the queries. We propose an algorithm, called RSQS, which allows the newly arrived query to best share the operations with existing queries. The simulation results showed that our proposed approach can be used to effectively reduce the amount of sensory data transmitted in the network. This leads to energy and bandwidth saving in wireless sensor network.

A Wireless Sensor network (WSN) consists of large number of low cost low power sensor nodes. The nature of wireless sensor networks makes them very attractive to attackers. One of the most popular and serious attacks in wireless sensor networks is sink hole attack and most existing protocols to defend against this attack used cryptographic methods with keys. In sink hole attack a sensor node will have a lot of false neighbors. Wireless Sensor Network has a dynamic topology, intermittent connectivity, and resource constrained device nodes. Researchers over the past years have encouraged the use of mobile agent to overcome these challenges. The proposed scheme is to defend against sink hole attacks using mobile agents. Mobile agent is a program segment which is self controlling. They navigate from node to node not only transmitting data but also doing computation. They are an effective paradigm for distributed applications, and especially attractive in a dynamic network environment. A routing algorithm with multiple constraints is proposed based on mobile agents. It uses mobile agents to collect information of all mobile sensor nodes to make every node aware of the entire network so that a valid node will not listen the cheating information from malicious or compromised node which leads to sink hole attack. The significant feature of the proposed mechanism is that it does not need any encryption or decryption mechanism to detect the sink hole attack. This mechanism does not require more energy than normal routing protocols like AODV. Here we implement a simulation-based model of our solution to recover from a Sinkhole attack in a Wireless Sensor Network. The mobile agents were developed using the Aglet.

In wireless sensor networks, preserving privacy is more important and has attracted more attentions. Protecting data and sensor privacy while collecting and computing query results is a challenge. In cluster-based sensor networks, when a user queries a sensitive data, the adversaries can monitor original node or gain the data in cluster node. To deal with this problem, we propose a secure and efficient scheme for cluster-based query processing in wireless sensor networks. To preserve location privacy of sensors, we use anonymity method to confuse adversaries. To protect the sensitive data, we use prefix membership verification method to prevent adversaries from gaining sensitive messages collected by sensor nodes. And we analyze the security and communication cost. The results show that our scheme can efficiently protect privacy in query processing.

Wireless sensor networks which are consisted of limited sensing, processing and communication equipments have prominent role in nowadays real-life applications. Efficient robust routing is a key feature in information processing in wireless sensor networks, especially in the presence of high-loss regions which occur due to harsh environment, hardware or software faults. In this paper, we propose a novel routing algorithm for high loss regions which have message loss above a given threshold. We solve theoretically the problem of near-optimal routing in a weighted region. Furthermore, Simulation experiments confirm the validity of proposed algorithm with high degree of accuracy.

In wireless sensor networks, the mobile agent technology is used in data transmission from one cluster to another cluster. The Optimization of mobile agent in the routing within the clustering algorithm for wireless sensor networks to further reduce the amount of data transfer. the main objectives of wireless sensor network design is to improve the energy efficiency & effective utilization of sensor nodes to prolong the lifespan of a wireless network .This paper presents an effective clustering algorithm, which is an extension to the LEACH routing algorithm., this algorithm fully utilizes the location information of network nodes in routing to reduce the routing cost. Through a clustering approach of intelligent mobile agents, it is possible to reduce the cost of time for each individual agent, here the problem of Multiple Clustering of Mobile Agents (MCCMA) where the decision is to cluster mobile agents such that a group of similar intelligent mobile agents will visit a group of similar sensor nodes are compare with location based clustering algorithm of wsn. both of Simulation results indicate that these algorithm & approach of mobile agent & wireless sensor network Nodes can have balance nodes' energy consumption and prolong the network's life span. It also has good extensibility & stability

This paper puts forward an optimization in routing processing for wireless sensor networks. The sensor node in such network is a battery-operated sensing device. These nodes are placed in space with a consideration to a base station that centralizes and consolidates the data transmitted or forwarded by sensor nodes. When optimizing the management of a Wireless Sensor Network, we have to take care of the consumption of energy that takes place while sensor nodes are running the routing process to send or relay a message to neighbors or to a Base Station. In this paper, we put forward a study of sensors' behavior by modeling and implementing a controller with Coloured Petri Network in order to ensure the reduction of energy consumption in some sensor networks in which each node can be activated or suspended as need be. The controller must deal with activation and suspension to apply a reconfiguring policy to nodes depending on an energy supply level in every sensor in order to obtain the lowest level possible of energy consumption and maintain the same service quality consisting in total coverage of the region to survey and the connection of active nodes to the functional network. The evaluation of our presented model is made by CPN-Tools.

A multi-Mobile Agent and optimal itinerary planning-based data aggregation in Wireless Sensor Networks

Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation due to the poor resources of traditional sensor nodes in WSNs. However, compared to the traditional sensor nodes, today’s devices for WSNs have more powerful resource. Thus, sensor nodes these days not only conduct sensing and transmitting data to servers but also are able to process many operations, so more diverse applications can be applied to WSNs. Especially, many applications using audio data have been proposed because audio is one of the most widely used data types, and many mobile devices already have a built-in microphone. However, many of the applications have a requirement that heavy-operations should be done by a tight deadline, so it is difficult for a single node in WSNs to run relatively heavy applications by itself. In this paper, to overcome this limitation of WSNs, we propose a new emerging system, HeaLow, a cooperative computing system for heavy-computation and low-latency processing in WSNs. We designed HeaLow and carried out the practical implementation on real devices. We confirmed the effectiveness of HeaLow through various experiments using the real devices and simulations. Using HeaLow, nodes in WSNs are able to perform heavy-computation processes while satisfying a completion time requirement.

In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data to the sink, MA presents a good alternative in terms of energy consumption, response time and network lifetime. In this paradigm, the most critical properties of MA is the itinerary planning, it has always been an issue and a NP-hard problem. In this paper, we present a survey of the proposed itinerary planning approaches for MAs in WSNs. MA itinerary planning techniques can be classified into three categories: static itinerary planning, dynamic itinerary planning and hybrid itinerary planing. The benefits and shortcomings of different MA itinerary planning approaches are presented. Furthermore, we implement, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions.

The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.

Wireless sensor networks (WSNs) have been proposed for a large variety of applications. As the number of applications of sensor networks continue to grow, the number of users in sensor networks increases as well. Consequently, it is not uncommon that base station often needs to process multiple queries simultaneously. Furthermore, these queries often need to collect data from some particular sets of sensors such as the sensors in a hot spot.To reduce the communication cost of multiple query processing in WSNs, this paper proposes a new optimization technique based on similarities among multiple queries. Given a set of queries, Q, the proposed scheme constructs a set of shared intermediate views (SIVs) from Q. Each SIV identifies a set of shared data among queries in Q. The SIVs, are processed only once, but reused by at least two queries in Q. The queries in Q, are rewritten into a different set of queries, Q ′. The collected sensor data from Q ′ and SIVs, are aggregated and returned as the processing results for the original set of queries in Q. The simulation results show that the proposed technique can effectively reduce the communication cost of multiple query processing in WSNs.KeywordsSensor NetworkSensor NodeWireless Sensor NetworkData TransmissionQuery ProcessingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Data aggregation is an important process for wireless sensor networks (WSNs). The important aspects with WSNs are to increase the lifetime and to reserve the battery power of sensor nodes. The energy of nodes is mainly utilized in the process of sensing and transmitting the data. Clustering is one of the processes in which the total WSNs are divided into the form of groups and each group has a cluster head (CH) and advantage of doing this is decrease of energy consumption and reduce the data collision. The blockchain technology is utilized in WSN by so many ways for example security, data storing, node recovery etc. because the role of blocks in blockchain is same as the role of node in WSN. In this paper, we propose a cluster-based data aggregation framework for wireless sensor networks based on the blockchain technique. The proposed scheme is based on cluster head (CH) selection based on energy, and nodes communicate with each other via the shortest path. Further, the proposed scheme is also using the concept of blockchain technology for the purpose of maximum data storage. KeywordsWireless sensor networksLow energy adaptive clustering hierarchy (LEACH)Data aggregationCluster headBlockchainAnd Energy consumption

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.

In wireless sensor network, many sensor nodes are distributed in the field. They communicate the sensing data each other and forward it to sink. Routing protocols, which define the delivery methods of sending data, affect to the lifetime of sensor network. This paper proposes RTAF that is a routing-tree construction algorithm of sensor nodes by a single flooding process in wireless sensor network. A routing tree is constructed by selecting a parent node using the forward-direction flooding packet and gathering children nodes using the reverse-direction flooding packet. In this process, a node with much energy becomes the parent node. And the routing tree is periodically reconstructed in order to distribute the loads of parent nodes. The proposed algorithm compared performance with Modified-LEACH using NS2 network simulation tool. The simulation result shows that the proposed algorithm constructs a routing-tree faster and reduced 40-80% in routing-tree construction packet.