The Hot Spot effect is an issue that reduces the network lifetime considerably. The network on the field forms a tree structure in which the sink represents the root and the furthest nodes in the perimeter represent the leaves. Each node collects information from the environment and transmits data packets to a "reachable" node towards the sink in a multi-hop fashion. The closest nodes to the sink not only transmit their own packets but also the packets that they receive from "lower" nodes and therefore exhaust their energy reserves and die faster than the rest of the network sensors. We propose a technique to allow the data sink to identify nodes severely suffering from the Hot Spot effect and to move beyond these nodes. We will explore the best trajectory that the data sink should follow. Performance results are presented to support our claim of superiority for our scheme.

In this thesis, we propose mechanisms to extend the lifetime of wireless sensor networks. In-network data aggregation is considered on both tree-based and flow-based routing protocols during the process of data collection to reduce redundant transmissions. In the flow-based data collection design, we introduce the concept of flow loss multiplier to express the impact of data aggregation over correlated data. The application has the freedom to set the flow loss multiplier to reflect its specific knowledge of correlation. We also introduce traffic balancing as a complementary technique to data aggregation. It helps avoid exhausting the energy of any sensor node while leaving large amounts of energy at other nodes. In tree-based data collection schemes, we adjust the tree structure judiciously to balance energy consumption before any node's failure due to total residual energy depletion. In flow-based schemes, after aggregation, data flows are split and the fragments are spread to increase network lifetime. We investigate the impact of performing greedily data aggregation at the "best" aggregation site regardless of its location, the results of our analysis show that only applying 2-way data aggregation may limit the ability to explore more complex aggregation possibilities. To address this problem, we propose an aggressive data aggregation for a specified application, contour map reconstruction. Based on the simulation results, our aggregation scheme is shown to be able to eliminate large volume of contour data and retain satisfying data accuracy.

Wireless Sensor Networking is envisioned as an economically viable paradigm and a promising technology because of its ability to provide a variety of services, such as intrusion detection, weather monitoring, security, tactical surveillance, and disaster management. The services provided by wireless senor networks (WSNs) are based on collaboration among small energy-constrained sensor nodes. The large deployment of WSNs and the need for energy efficient strategy necessitate efficient organization of the network topology for the purpose of balancing the load and prolonging the network lifetime. Clustering has been proven to provide the required scalability and prolong the network lifetime. Due to the bottle neck phenomena in WSNs, a sensor network loses its connectivity with the base station and the remaining energy resources of the functioning nodes are wasted. This thesis highlights some of the research done to prolong the network lifetime of wireless sensor networks and proposes a solution to overcome the bottle neck phenomena in cluster-based sensor networks. Transmission tuning algorithm for a cluster-based WSNs is proposed based on our modeling of the extra burden of the sensor nodes that have direct communication with the base station. Under this solution, a wireless sensor network continues to operate with minimum live nodes, hence increase the longevity of the system. An information theoretic metric is proposed as a cluster head selection criteria for breaking ties among competing clusters, hence as means to decrease node reaffiliation and hence increasing the stability of the clusters, and prolonging the network lifetime. This proposed metric attempts to predict undesired mobility caused by erosion.

Wireless Sensor Networking is envisioned as an economically viable paradigm and a promising technology because of its ability to provide a variety of services, such as intrusion detection, weather monitoring, security, tactical surveillance, and disaster management. The services provided by wireless senor networks (WSNs) are based on collaboration among small energy-constrained sensor nodes. The large deployment of WSNs and the need for energy efficient strategy necessitate efficient organization of the network topology for the purpose of balancing the load and prolonging the network lifetime. Clustering has been proven to provide the required scalability and prolong the network lifetime. Due to the bottle neck phenomena in WSNs, a sensor network loses its connectivity with the base station and the remaining energy resources of the functioning nodes are wasted. This thesis highlights some of the research done to prolong the network lifetime of wireless sensor networks and proposes a solution to overcome the bottle neck phenomena in cluster-based sensor networks. Transmission tuning algorithm for a cluster-based WSNs is proposed based on our modeling of the extra burden of the sensor nodes that have direct communication with the base station. Under this solution, a wireless sensor network continues to operate with minimum live nodes, hence increase the longevity of the system. An information theoretic metric is proposed as a cluster head selection criteria for breaking ties among competing clusters, hence as means to decrease node reaffiliation and hence increasing the stability of the clusters, and prolonging the network lifetime. This proposed metric attempts to predict undesired mobility caused by erosion.

No description available.

In this thesis, we consider cognitive radio networks (CRN) combined with cooperative transmission, and investigate relay selection and power allocation strategies to maximize network lifetime (NLT). Cognitive radio network enhances spectrum efficiency resource by exploiting capabilities of cognition, learning and coordination against insufficient spectrum resource. In underlay cognitive radio network, however, transmitted energy of secondary user is constrained by interference level observed at primary user (PU). Though cooperation among secondary users (SU), multiple relays from virtual antenna array to improve transmission rate and reliability by exploiting spatial diversity. Most existing works assume that cooperative secondary users are plugged and with infinite energy device. In this thesis, we consider secondary cooperative systems where relays are battery-powered and with finite energy. We will investigate relay-selection schemes to reduce energy consumption of secondary relays and prolong network lifetime under the premises that secondary user¡¦s transmission rate is guaranteed and interference constraint of primary user is met. Our major difference between this work and previous works is the definition of network lifetime, which is defined by the maximum duration that the probability of secondary user¡¦s achievable rate below the guaranteed value, i.e. outage probability, is lower than a predetermined threshold. We proposed four relay-selection methods which take channel state information (CSI) and residual energy information (REI) into considerations to prolong network lifetime. Since the selection metrics of the proposed strategies requires CSI and REI of each individual relay, so the relay-selection can be accomplished in distributed manner through opportunistic sensing. No additional overhead is demanded for information exchange.

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) 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.

Wireless Sensor Networks (WSNs) overcome the difficulties of other monitoring systems, as they require no human attendance on site, provide real-time interaction with events, and maintain cost and power efficient operations. However, further efficiencies are required especially in the case of Outdoor Environment Monitoring (OEM) applications due to their harsh operational conditions, huge targeted areas, limited energy budget, and required Three-Dimensional (3D) setups. A fundamental issue in defeating these practical challenges is the deployment planning of the WSNs. The deployment plan is a key factor of many intrinsic properties of OEM networks, summarized in connectivity, lifetime, fault-tolerance, and cost-effectiveness. In this thesis, we investigate the problem of WSNs deployments that address these properties in order to overcome the unique challenges and circumstances in OEM applications. A natural solution to this problem is to have multiple relay nodes that reserve more energy for sensing, and provide vast coverage area. Furthermore, assuming a subset of these relay nodes are mobile can contribute in repairing the network connectivity problems and recovering faulty nodes, in addition to granting balanced load distributions, and hence prolonging the network lifetime. We investigate this promising research direction by proposing a 3D grid-based deployment planning for heterogeneous WSNs in which Sensor Nodes (SNs) and Relay Nodes (RNs) are efficiently deployed on grid vertices. Towards this efficiency, we analyze and characterize the grid connectivity property in the 3D space. Afterward, we design optimization schemes for the placement of SNs and RNs on the 3D grid models. Based on theoretical analysis and extensive simulations, the proposed schemes show a significant enhancement in terms of network connectivity and lifetime in OEM applications. / Thesis (Ph.D, Computing) -- Queen's University, 2011-05-02 10:29:01.785

<p>Denna avhandling handlar om hur befintliga datorinfrastrukturer i t.ex. sjukhus och industrier kan avlasta sensornätverk med energikrävande uppgifter. Vi har forskat på olika aspekter som gör det möjligt att förlänga livslängden på dessa sensornätverk. Avhandlingen presenterar en ny plattform för sensornätverk tillsammans med inledande simuleringar som påvisar att vår plattform ökar livslängden på dessa typer av nätverk.</p><p>Generella sensornätverk är uppbyggda av tätt grupperade, trådlösa, batteridrivna datorer som kan vara så små som en kubikmillimeter. Datorerna kallas för sensorer eller sensornoder eftersom de har en eller flera inbyggda sensorer som känner av sin omgivning. En sensor har till uppgift att samla information från sin omgivning, t.ex. temperatur, fuktighet, vibrationer, hjärtslag eller bilder. Sensorerna skickar sedan informationen till en insamlingsstation någonstans i nätverket.</p><p>I de typer av tillämpningar vi tittar på är det viktigt att minimera energiförbrukningen, så att man maximerar livslängden på sensornätverket. Avhandlingen presenterar en lösning där befintlig datorinfrastruktur fungerar som hjälpdatorer/avlastare till ett sensornätverk. Hjälpdatorerna, eller basstationerna som vi kallar dem i avhandlingen, hanterar energikrävande uppgifter som t.ex. vilken sensor som ska kommunicera med vem samt vid vilken tidpunkt etc. Då kan sensorerna i nätverket fokusera på att utföra sina egna uppgifter tills dess att basstationen säger att uppgifterna ändrats.</p><p>Simuleringar visar att vår plattform kan skicka upp till 97 % mera information till basstationen än en jämförbar plattform med samma energimängd. 88 % av våra sensorer är fortfarande vid liv när den andra plattformens sensorer förbrukat all sin energi.</p><p>Ett exempel på hur dessa typer av nätverk kan användas är att övervaka patienters hälsa och kondition i sjukhus eller sjukhem. Patienter behöver inte ha en fast sängplats där en viss typ av medicinskt övervakningsinstrument finns tillgänglig utan kan placeras där det finns en ledig sängplats. Via trådlös kommunikation skickar sensorerna sedan hälsoinformation som t.ex. hjärtfrekvens och blodtryck till en basstation som i sin tur skickar vidare till ett centralt övervakningsinstrument någonstans på sjukhuset. Övervakningsinstrumentet behandlar informationen och larmar personal med rätt kompetens vid behov. Larmet kan skickas till en mobiltelefon eller en liten handdator som personalen alltid bär med sig. Med larmet skickas även information om var patienten befinner sig och all nödvändig data för att personalen snabbt ska kunna ställa en första diagnos. På detta sätt kan man spara in på antalet specialbyggda sängplatser och slippa dyrbara installationer av medicintekniska utrustningar knutna till en sängplats.</p> / <p>Recent advancements in electronic design, such as low-power circuits, energy efficient wireless communication, and improved energy supply, has enabled the vision of wireless sensor networks to become a reality. Wireless sensor networks typically consist of hundreds up to thousands of collaborating low-cost, battery-driven and wireless sensor nodes with scarce resources. The wireless sensor nodes are typical small physical entities, and usually small as a matchbox but can in extreme cases be no larger than a cubic millimeter.</p><p>In this thesis we present an architecture called AROS that uses existing infrastructure to aid in the management of wireless sensor networks. As an example, the existing infrastructure could be situated in hospitals or industrial buildings. The existing infrastructure can aid in prolonging the lifetime of the wireless sensor network by having "unlimited'' energy, long range radio capacity, and high-speed computers. We enable prolonged lifetime by centralizing some of the energy consuming administrative functionality of wireless sensor networks.</p><p>We show, by simulations, that the AROS architecture is able to prolong the lifetime of the sensor nodes. AROS is compared to a well known cluster based architecture, LEACH. The comparisons show that AROS with static configuration performs at least as well as LEACH in small wireless sensor networks in the size 100x100m, and up to 97 % better in long distance wireless sensor networks in the size of 400x400m. We show that AROS still has got 88 % of its sensor nodes alive when LEACHs' network demises.</p><p>In our simulations we have also studied how dynamic network clustering in AROS, using a TDMA scheduler and non-mobile wireless sensor nodes, affects the amount of data received by a base station. We show that AROS is better than LEACH-C in collecting data to the base station with the same total amount of energy for long distance networks and that AROS performs as well or better than LEACH-C in small wireless sensor networks.</p>