Energy-efficient data redistribution in sensor networks

In large-scale Wireless Sensor Networks (WSNs) the amount of data gathered require energy efficient data dissemination and data retrieval techniques. Data Centric Sensor (DCS) networks is a better approach in which the sensed data are sent to a sensor node whose name is associated with sensed data. Due to unattended nature of Wireless Sensor Networks, these sensor nodes are susceptible to different types of attacks. In this paper we propose a Secure Data Centric Sensor (SDCS) Networks that includes security and privacy support to DCS networks. In addition, we propose a multi-query optimization technique that aggregates similar queries and reduces the number of messages. Simulation and experimental results show that our work provides a secure data centric sensor network based on cryptographic keys and reduces the message overhead and incurs a minimum communication cost compared to previous works.

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

Multi-constraint multi-objective QoS aware routing heuristics for query driven sensor networks using fuzzy soft sets

Sensor networks are multi hop wireless networks formed by a large number of resource-constrained sensor nodes. The events detected by the sensor generate a stream of data. Centralized join query processing algorithm incur more communication overhead due to frequent exchange of data between the sink and the sensor nodes. To query or access data generated by the sensor nodes, the sensor network can be viewed as a distributed database. Communication-efficient implementation for join of multiple data streams in a sensor network is particularly challenging due to unique characteristics of the sensor networks such as limited memory and battery energy on individual nodes. Hence the design of Distributed Nested Loop Join Processing (DNLJP) algorithm has been proposed in this paper. The proposed scheme groups sensors based on geographic locations to form a cluster and perform the query processing in a distributed manner over the data collected across different regions. DNLJP also optimizes the query based on the desired optimization criteria like query cost, query execution time etc., and applies the corresponding query processing technique to achieve the desired result. Analysis shows that the communication overhead of the proposed distributed algorithm is reasonably low and the efficiency of the query processing is considerably improved over a wide range of query.

There are performance deficiencies that hamper the deployment of Wireless Sensor Networks (WSNs) in critical monitoring applications. Such applications are characterized by considerable network load generated as a result of sensing some characteristics of the monitored system. Excessive packet collisions lead to packet losses and retransmissions, resulting in significant overhead costs and latency. In order to address this issue, we introduce a distributed and scalable scheduling access scheme that mitigates high data loss in data-intensive sensor networks and can also handle some mobility. Our approach alleviates transmission collisions by employing virtual grids that adopt Latin Squares characteristics to time slot assignments. We show that our algorithm derives conflict-free time slot allocation schedules without incurring global overhead in scheduling. Furthermore, we verify the effectiveness of our protocol by simulation experiments. The results demonstrate that our technique can efficiently handle sensor mobility with acceptable data loss, low packet delay, and low overhead.

Sensor devices have been widely applied to variety applications, including internet of things (IoT), cyber physical systems (CPS) and environmental monitoring systems. Because all sensing data in such applications are very important for data analysis and mining in a host machine, sensor devices are equipped with non-volatile memory (NVM) [1] and nonvolatile processor [2], [3] to prevent sensing data in sensor nodes from data loss. As a result, sensing data can be permanently stored in a sensor device without the risk of data loss even if the battery of the sensor device is run out. Based on such observations, the lifetime of a sensor network should be redefined due to non-volatile technologies, such as NVM and NV processor. Conventionally, the lifetime of a sensor network is the time at which the first sensor node uses up its battery due to the consideration of sensor network QoS [4], [5]. However, since sensing data can be permanently stored in a local drive, the lifetime of a sensor network should be redefined as the time at which the first out-of-date data is produced in a sensor node. If the battery of a sensor node is run out but the sensor node does not contain any out-of-date data, the sensor node will be regarded as a moribund node. If all moribund nodes can be rescued by a rechargeable technology, the sensor network will be immortal. Such observations motivate us to design an energy-efficient solution to achieve the goal of immortal sensor network by exploiting the benefits of wireless charging vehicle.

Providing a powerful synchronization system is one of the most important goals to be pursued if an efficient utilization of sensor networks has to be addressed. The basic concept behind a Wireless Sensor Network is to deploy a large number of sensor nodes able to acquire and process data. Most of WSNs applications require sensor nodes to maintain local clocks both to determine the events order and to provide temporal information to measured data; to achieve this goal applications generally require a low synchronization precision, close to Milli seconds. This paper proposes a novel synchronization system based on Kohonen's Self Organizing Maps (SOMs), able to provide some Artificial Intelligence features to sensor nodes. A SOM is a particular neural network that learns to classify data without any supervision. In each sensor node, a SOM is implemented to evaluate the sensor node time, using a very little amount of storage and computing resources. In a scenario where thousands of sensor nodes are placed, this system evaluates the time of each sensor in a distributed manner, assuming a very little percentage of nodes knowing the actual time, thus ensuring an effective clock synchronization among all the sensors.

In recent days the wireless sensor nodes are implemented in various applications. Formation of wireless network using sensor nodes facing a lot of real time issues like energy computation and communication overhead. The sensor nodes are powered up by battery sources. Once the sensor node is deployed in real time environment, changing the battery source like clockwork is not possible. Hence finest cluster architecture was developed for node connection, node communication and to implement energy efficient wireless sensor network. In the proposed work the sensor nodes are designed with ARM LPC2148 processors which support the real time emulation and embedded trace. Using this sensor node, an optimised wireless network was developed with experimental set up. The proposed hardware was tested and various evaluation factors are analysed. Problems related with the design of sensor nodes and network establishment is explained. Depending upon the application, sensor node has to be incorporated into the network.

Wireless Sensor Networks (WSNs) consists of low power nodes, with limited processing, communication, and storage. The networks are made up of tiny nodes which are becoming future of many applications, but due to deployment nature the sensor nodes are prone to physical attacks against the adversaries and resource limitations raises some serious question to secure these nodes. Random failure of nodes occurred in real-life deployment scenarios. Due to the resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security is a challenging task in WSN and basic security goals in sensor networks are Confidentiality, Integrity, Authentication and Availability (CIAA). Many security solutions have been proposed in the domain so far. Due to a number of physical constraints in sensor nodes, traditional cryptographic mechanisms are not suitable to deal with such potential security threats. This paper is devoted to the research on security efficiency for wireless sensor networks. The proposed scheme of Individual Pairwise and Cluster (IPC) key management is based on the generation and distribution of the individual key, pairwise key and the cluster head broadcast key. This paper proposes a solution which uses the basic scheme, but does not use group-based deployment model and pre-deployment knowledge of the locations of nodes, and yet performs better than the schemes which uses the group-based deployment. The security analysis shows that the scheme within this paper meets the unique security needs of the sensor networks.

Sensor nodes used to transmit sensitive data, especially in military applications, require securing the data transmitted through the WSNs to maintain the confidentiality of the data and authenticate the participating sensor nodes. Since sensor nodes suffer from limited resources, in memory storage, computing power, energy capabilities and transmission rates, available network security protocols are inadequate. Symmetric algorithms cannot provide the same degree of security as public key algorithms, leading us to devise a new algorithm SHESP that uses public keys within the limitations of sensor nodes. This paper presents a way to utilise existing public key algorithms such as RSA, Diffie-Hellmann and elliptic curve in the field of WSN security by dividing the network into clusters. Our algorithm supplies data confidentiality, node authentication and data integrity while remaining within acceptable memory, time and energy constraints. We provide theoretical and experimental evidence to validate our algorithms. Results reveal significant improvement in data availability, data confidentiality and authenticity while reducing the communication and computation overhead.

Sensor network is one of the authoritative leading technology of current century. Security is the main concern for everything whether it is for wired based networks or wireless based networks. So far, many of the researches have thought to physically implement the sensor nodes and sensor networks for secure communications but they did not think over it for security perspective. Sensor network works in very resource constraint environment. Due to these security reasons, we present various protocols to provide the basic needs of data security that are: confidentiality, authentication, freshness and authenticated broadcasting because this broadcasting requires some techniques or protocols to securely communicate with other sensor node(s). Other issues in sensor networks are power management, computation overhead and low memory capacity.

A large number of potential applications for Wireless Sensor and Actuator Networks (WSAN) have yet to be embraced by industry despite high interest amongst academic researchers. This is due to various factors such as unpredictable costs related to development, deployment and maintenance of WSAN, especially when integration with existing IT infrastructure and legacy systems is needed. Service-Oriented Architecture (SOA) is seen as a promising technique to bridge the gap between sensor nodes and enterprise applications such as factory monitoring, control, and tracking systems where sensor data is used. To date, research efforts have focused on middleware software systems located in gateway devices that implement standard service technology, such as Devices Profile for Web Services (DPWS), for interacting with the sensor network. This paper takes a different approach-deploying interoperable Simple Object Access Protocol (SOAP)-based web services directly on the nodes and not using gateways. This strategy provides for easy integration with legacy IT systems and supports heterogeneity at the lowest level. Twofold analysis of the related overhead, which is the main challenge of this solution, is performed; Quantification of resource consumption as well as techniques to mitigate it are presented, along with latency measurements showing the impact of different parts of the system on system performance. A proof-of-concept application using Mulle-a resource-constrained sensor platform-is also presented.

Target tracking is one of the most important applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to maximize the lifetime of the sensor network. There exists a demand for self-organizing and routing capabilities in the sensor network. Existing methods attempting to achieve these requirements, such as the LEACH-based algorithms, however, suffer either redundancy in data and sensor node deployment, or complex computation incurred in the sensor nodes. Those drawbacks result in energy use inefficiency and/or complex computation overhead. OCO, or Optimized Communication and Organization, is an algorithm that ensures maximum accuracy of target tracking, efficient energy dissipation, and low computation overhead on the sensor nodes. Simulation evaluations of OCO are compared with other two methods under various scenarios.

In the paper, we consider a network of energy- constrained sensors deployed over a region. Each sensor node in such a network is systematically gathering and transmission sensed data to a base station (via clusterhead) for further processing. A key challenge in data gathering is to maximize the system lifetime, given the energy constraints. We focus on reducing the power consumption of wireless sensor networks. The dominate component in energy consumption is almost always due to communication. Therefore, we heavily modify an exist- ing communication protocol, Low-Energy Adaptive Clustering Hierarchy (LEACH). We extend LEACH's stochastic cluster- head selection algorithm by a deterministic component to reduce energy consumption. Simulation results show that our modified scheme can extend the network life around 50% for First Node Dies (FND) and 62% for Last Nodes Dies (LND). Index Terms-Wireless sensor networks, energy efficiency, cluster- head selection, LEACH I. INTRODUCTION Wireless sensor network consists of hundreds to several thousands of small sensor nodes scattered throughout an area of interest. Sensor nodes may spontaneously create impromptu network, assemble the network themselves, dynamically adapt to device failure and degradation, manage movement of sensor nodes, and react to changes in task and network requirements. Each individual sensor contains both processing and communi- cation elements and is designed to monitor the environment for events specified by the deployer of the network. Information

Background: Internet of Things (IoT) is the next emerging technique in which each and every thing in the world is getting connected to the internet by means of various communication techniques. By using the technique of multicasting, these things communicate with each other to transfer the data. So there is a need of an authentication scheme in order to prevent the data form getting corrupted while transmitting. As we know trillions of devices are connected in IoT, a secure communication should be implemented for the same. So a light weight authentication should be provided for IoT. Methods: The IoT consist of many objects, the objects may me mobile phones, refrigerator, air cooler etc. along with sensors, actuators, base station. The objects are mainly connected with sensors in order to retrieve data from each of them. Since sensor network is adhoc networks and the computational power consumed of sensor networks are also very low. Hence in the Wireless Sensor Network (WSN) many sensors are connected with one or more base station. The base station in wireless sensor network manages all the sensor nodes with the help of processor and memory. Since we are transforming from wireless sensor networks to IoT, the objects are connected to internet by providing address to individual object. So, the base station not having the capable to provide a secure communication between the objects along with sensors and internet.In this paper, we propose a new authentication scheme by means of two different approaches. Since IoT contains many numbers of objects, we connect certain objects which are in same area and provide a database for that object. The data related to particular node is stored and updated frequently in the database and maintained by Data Base Management System (DBMS) and it is connected to internet. Results: Whenever a user wants to access the data, the authentication is provided by means of login id with hashing password or with the help of MAC passwords. These two authentication scheme provide better when compared to existing method which are shown in results. The metrics that measures the performance of the proposed approach are the resistance against node compromise,computation overhead,communication overhead, robustness to packet loss and message entropy. Applications: This main application of mutual authentication scheme for IoT is to provide a authentication between the end user and the sensor network data. This method is also suitable for smart house application where the user can securely access the data from anywhere in the world.