Exploitation of wireless sensor networks (WSNs) in ubiquitous computing environments is continuously increasing for gathering data. Contemporary distributed software systems on WSNs for pragmatic business applications have become extremely adaptive, dynamic, heterogeneous and large scaled. Management of such system is not trivial to fulfil these features, leading to more and more complex management and configuration. Along with encompassing state of art and novel techniques for such diversely dynamic system, in this thesis two alternative techniques namely “task initiation by command” and “run-time task deployment and processing” are compared, for such system’s setup and configuration. Both techniques have their own pros and cons which makes them suitable according to the requirements and contextual situations. A lot of effort has been put to make WSNs more and more efficient in terms of computations and power consumption. Hence comparative analysis of both techniques used in this report to setup and configure WSN can be a benchmark to lead towards most appropriate solution to compensate the need of efficient energy and resource consumption.Both alternative schemes are implemented to setup WSN on Sun Microsystems sunSPOT (Small Programmable Object Technology) sensor nodes which are embedded microcontrollers and programmed them in java (j2me). It performs radio communication between wireless sensors and host via sink node also called base station, along with over the air run-time management of sensors. SunSPOTs built in libraries and KSN libraries are used to implement these alternatives and compare the memory footprint, communication pattern and energy consumption.Exploitation of wireless sensor networks (WSNs) in ubiquitous computing environments is continuously increasing for gathering data. Contemporary distributed software systems on WSNs for pragmatic business applications have become extremely adaptive, dynamic, heterogeneous and large scaled. Management of such system is not trivial to fulfil these features, leading to more and more complex management and configuration. Along with encompassing state of art and novel techniques for such diversely dynamic system, in this thesis two alternative techniques namely “task initiation by command” and “run-time task deployment and processing” are compared, for such system’s setup and configuration. Both techniques have their own pros and cons which makes them suitable according to the requirements and contextual situations. A lot of effort has been put to make WSNs more and more efficient in terms of computations and power consumption. Hence comparative analysis of both techniques used in this report to setup and configure WSN can be a benchmark to lead towards most appropriate solution to compensate the need of efficient energy and resource consumption.Both alternative schemes are implemented to setup WSN on Sun Microsystems sunSPOT (Small Programmable Object Technology) sensor nodes which are embedded microcontrollers and programmed them in java (j2me). It performs radio communication between wireless sensors and host via sink node also called base station, along with over the air run-time management of sensors. SunSPOTs built in libraries and KSN libraries are used to implement these alternatives and compare the memory footprint, communication pattern and energy consumption.

Radio Frequency Identification (RFID) technology is an electronic labeling technique.These electronic labels are called tags and read wirelessly. In this thesis a battery and amicroprocessor are connected to the tag. The work consisted of programming themicroprocessor to transfers sensor data into the tags memory. The tags are placed ontrains and data is collected from sensors at the train's axle. That way sensor data can betransmitted from a train to readers stationed along the railroad tracks.The aim of the project is to predict service intervals. There is currently no possibility tosee wear in real time and stop a train before it breaks. At present, there is a form of heatdetectors located along the railroad tracks to measure temperatures of wheels and axlesof passing trains. These are expensive and have the disadvantage of being able to detecterrors that have already occurred, they can not detect errors that do not radiate heat.The thesis aims to provide a solution for this. By programming a microprocessor totransmit sensor data to the tags memory it is possible for an RFID reader to read thesensor data from the tag. Ensuring that data and identity can be read from the tag atspeeds up to 250 km/h, you can get the status of a trains wagon before it breaks.

In recent years, the development of wireless sensor networks has made a great progress. Early projects focused on replacement of existing systems equipped with wires. These systems started out as simple static data collection networks with one smart central node that could decide further actions based on the content of the collected data. Through time, the intelligence has become more decentralized, which means the nodes now can cooperate in a more efficient and dynamic manner. The task given is to evaluate TinyOS and NesC on specific hardware from Crossbow Technology Inc, applied on an application called the Open Secure Office Project. This application is designed to enhance the security without negative effects on comfort in a frequently visited open-plan office. Finally, a real world system demonstration should be performed. We propose a solution where there is no urgent need to cover the entire office area with radio signals to maintain a secure sensor system. This is true as long as all entries and exits to the office area are “guarded” by some base station which has as main task to keep track of people and equipment entering or leaving the office. Small scale tests have been performed which show that it is possible to easily develop and maintain a wireless sensor network security system, that could be coordinated by alternative systems.

Wireless sensor networks offer easy implementation, flexibility and mobility of hand held devices. Sensors consist of an internal power source, which is the great limitation for the life time and the usage of sensor networks. To increase the life time, sensors should stay in energy saving sleep mode as long as possible, because in sleep mode the radio is either shut down or working with less energy. Better energy handling is implemented in different power saving mechanism of common Medium Access Control protocols, which are evaluated and analyzed and further extensions and ideas to improve the energy efficiency are presented. Slotted PSM is simulated with the NS2 and compared to the WLAN 802.11 PSM technology and the results show that energy efficiency and power consumption are much better implemented and life time increases with the use of Slotted PSM.

An achievable rate region for general wireless sensor networks is proposed. A general multi-source, multi-relay, multi-destination wireless sensor network with arbitrarily correlated sources is considered. Each node can sense some real phenomena and send its readings to one or more sinks (data gathering nodes) via some relays. It also can relay some correlated or independent readings of other nodes, simultaneously. In this problem the source and channel coding separation is not optimal and the information which each reading has about others nodes is destroyed in separation. Thus, a joint source channel coding scheme can be used. The problem consists of relay channels and multiple access channels with arbitrarily correlated sources. The proposed scheme is based on regular block Markov encoding/backward decoding and code division multiple-access (CDMA) and the result is a combination of multi-relay and multiple-access with correlated sources.

With the advances of wireless communications and micro-electronic device technologies, wireless sensor networks have been applied in a wide spectrum of applications, including one of the killer applications--object tracking. Among numerous challenges in object tracking, one of the important issues is the energy management. One solution to the above issue is the mobile agent-based paradigm. Using the mobile agent in wireless sensor networks has many advantages over the client/server paradigm in terms of energy consumptions, networks band-width, etc. In this thesis, we adopt the mobile agent-based paradigm to support object track-ing in wireless sensor networks. Although using the mobile agents for object tracking can improve the overall perfor-mance, the hurdle is the determination of the mobile agent itinerary. The past studies on ob-ject tracking considered the object¡¦s movement behavior as randomness or the direction and the speed of the object remain constant for a certain period of time. However, in most real-world cases, the object movement behavior is often based on certain underlying events rather than randomness complete. With this assumption, the movements of objects are some-times predictable. Through the prediction, the mobile agent can determine which node to mi-grate in order to reduce energy consumption and increase the performance of object tracking. In this thesis, we develop a mining-based approach to discover the useful patterns from the object¡¦s movement behavior. This approach utilizes the discovered rules to choose the sensor node the mobile agent needs to migrate in order to reduce the number of wrong migration, to reduce total energy consumed by sensor nodes, and to prolong the lifetime of the wireless sensor network. Experimental results show the efficiency of the proposed approach.

Smart devices with multiple on-board sensors, networked through wired or wireless links, are distributed in physical systems and environments. Broad applications of such sensor networks include manufacturing quality control and wireless sensor systems. In the operation of sensor systems, robust methods for retrieving reliable information from sensor systems are crucial in the presence of potential sensor failures. Existence of sensor redundancy is one of the main drivers for the robustness or fault tolerance capability of a sensor system. The redundancy degree of sensors plays two important roles pertaining to the robustness of a sensor network. First, the redundancy degree provides proper parameter values for robust estimator; second, we can calculate the fault tolerance capability of a sensor network from the redundancy degree. Given this importance of the redundancy degree, this dissertation presents efficient algorithms based on matroid theory to compute the redundancy degree of a clustered sensor network. In the efficient algorithms, a cluster pattern of a sensor network allows us to decompose a large sensor network into smaller sub-systems, from which the redundancy degree can be found more efficiently. Finally, the robustness analysis as well as its algorithm procedure is illustrated using examples of a multi-station assembly process and calibration of wireless sensor networks.

Hundred and thousands of wireless sensor node comprise wireless sensor network (WSN), WSN can be applied in many situations, because a wireless sensor node have small size and wireless transmission advantages, the battery provide sensor node power, but the battery¡¦s power is limit, therefore, energy efficiency is a critical issue, routing protocol can make better energy consumption and loading balance, Clustering is useful routing protocol in WSN and provides the direction of energy efficiency. The ARC (Adaptive Re-Clustering) is based on clustering; ARC can reduce the whole WSN power consumption and protect less residue power cluster-head. The experiments prove that ARC can improve network reliability and extend network lifetime.

Wireless Sensor Network (WSN) has become a popular wireless technology in recent years. In WSN, a large number of sensors are used to collect data and forward data hop-by-hop to a sink. Due to the unbalancing of traffic load, some grid nodes may consume more energy and their packet loss ratio may be increased as well. In order to improve above-mentioned shortcomings, in this Thesis, we propose an Adaptive Grid-based Data Collection (AGDC) scheme. Because a mobile sink may move, it is possible the traffic load of primary grid nodes can be changed in WSN. According to the distribution of traffic load, the AGDC can adjust transmission range to allocate one or more temporary grid nodes between two primary grid nodes. Through the added temporary grid nodes, traffic load is evenly dispersed among different grid nodes. We allow the primary grid nodes to use smaller transmission power to save energy and allow the temporary grid nodes to buffer data to reduce packet loss ratio. For the purpose of evaluation, we perform simulation on NS-2. With the proposed AGDC scheme, the transmission range of a primary grid node can be set to an appropriate distance to reduce power consumption and packet loss ratio. Since the packet loss ratio is reduced, the throughput of entire WSN is increased.

Wireless Sensor Network (WSN) is composed of micro sensor nodes and it represents that they are small in size and cheap in cost but own limited capacity of computation and operation time. WSN is used to detect and sense events like temperature, earthquake, creature activities, atmospheric pressure and so on. By the property of wireless data transmission, WSN can be rapidly deployed and easily built up. In other hand, lifetime of WSN has been constrained by the batteries built in each sensor node. To transmit sensed data back to the base station spends the most energy for the WSN, and thus how to operate efficiently will be the key to extend the operating time of the WSN. There are a lot of related researches that proposed many routing protocols to maximize WSN lifetime and clustering is a proven routing protocol for WSN energy efficiency. The clustering method group nearby nodes together and choose one of them as a cluster-head that will transmit data back. The most important issue of clustering method is to choose which as a cluster-head. Usually, cluster-head will be chosen by probability and normal nodes will choose their own cluster-head by distance. Global-fit and Energy-Efficient (GFEE) algorithm, which is based on global-fit concept, is proposed to enhance lifetime of WSN. GFEE not only chooses cluster-head by probability and taking turns, but also bases on residual energy. All other nodes choose their cluster-head by distance and total energy consumption. Nodes with low power should be protected by some mechanisms. Experiments approved GFEE, especially in the situations of nodes widely spread or long distance transmission.