Distributed Database Management Techniques for Wireless Sensor Networks

Authors and/or their employers shall have the right to post the accepted version of IEEE-copyrighted articles on their own personal servers or the servers of their institutions or employers without permission from IEEE, provided that the posted version includes a prominently displayed IEEE copyright notice and, when published, a full citation to the original IEEE publication, including a link to the article abstract in IEEE Xplore. Authors shall not post the final, published versions of their papers.In sensor networks, the large amount of data generated by sensors greatly influences the lifetime of the network. In order to manage this amount of sensed data in an energy-efficient way, new methods of storage and data query are needed. In this way, the distributed database approach for sensor networks is proved as one of the most energy-efficient data storage and query techniques. This paper surveys the state of the art of the techniques used to manage data and queries in wireless sensor networks based on the distributed paradigm. A classification of these techniques is also proposed. The goal of this work is not only to present how data and query management techniques have advanced nowadays, but also show their benefits and drawbacks, and to identify open issues providing guidelines for further contributions in this type of distributed architectures.This work was partially supported by the Instituto de Telcomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, by the Ministerio de Ciencia e Innovacion, through the Plan Nacional de I+D+i 2008-2011 in the Subprograma de Proyectos de Investigacion Fundamental, project TEC2011-27516, by the Polytechnic University of Valencia, though the PAID-05-12 multidisciplinary projects, by Government of Russian Federation, Grant 074-U01, and by National Funding from the FCT-Fundacao para a Ciencia e a Tecnologia through the Pest-OE/EEI/LA0008/2013 Project.Diallo, O.; Rodrigues, JJPC.; Sene, M.; Lloret, J. (2013). Distributed Database Management Techniques for Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems. PP(99):1-17. https://doi.org/10.1109/TPDS.2013.207S117PP9

Power efficiency through tuple ranking in wireless sensor network monitoring

In this paper, we present an innovative framework for efficiently monitoring Wireless Sensor Networks (WSNs). Our framework, coined KSpot, utilizes a novel top-k query processing algorithm we developed, in conjunction with the concept of in-network views, in order to minimize the cost of query execution. For ease of exposition, consider a set of sensors acquiring data from their environment at a given time instance. The generated information can conceptually be thought as a horizontally fragmented base relation R. Furthermore, the results to a user-defined query Q, registered at some sink point, can conceptually be thought as a view V . Maintaining consistency between V and R is very expensive in terms of communication and energy. Thus, KSpot focuses on a subset V′ (⊆ V ) that unveils only the k highest-ranked answers at the sink, for some user defined parameter k. To illustrate the efficiency of our framework, we have implemented a real system in nesC, which combines the traditional advantages of declarative acquisition frameworks, like TinyDB, with the ideas presented in this work. Extensive real-world testing and experimentation with traces from University of California-Berkeley, the University of Washington and Intel Research Berkeley, show that KSpot provides an up to 66% of energy savings compared to TinyDB, minimizes both the size and number of packets transmitted over the network (up to 77%), and prolongs the longevity of a WSN deployment to new scales

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

Semantics-Aware Services for the Mobile Computing Environment

Today's wireless networks and devices support the dynamic composition of mobile distributed systems according to networked services and resources. This has in particular led to the introduction of a number of computing paradigms, among which the Service-Oriented Architecture (SOA) seems to best serve these objectives. However, common SOA solutions restrict considerably the openness of dynamic mobile systems in that they assume a specific middleware infrastructure, over which composed system components have been pre-developed to integrate. On the other hand, the Semantic Web introduces a promising approach towards the integration of heterogeneous components; current semantics-based approaches are, however, restricted to application-level interoperability. Combining the elegant properties of software architecture modeling with the semantic reasoning power of the Semantic Web paradigm, this paper introduces abstract semantic modeling of mobile services that allows both machine reasoning about service composability and enhanced interoperability at both middleware and application level

Analysis of the energy latency trade-off in wireless sensor networks

Wireless Sensor Networks (WSNs) haben im letzten Jahrzehnt eine erhebliche Aufmerksamkeit erlangt. Diese Netzwerke zeichnen sich durch begrenzte Energieressourcen der Sensorknoten aus. Daher ist Energieeffizienz ein wichtiges Thema in Systemdesign und -betrieb von WSNs. Diese Arbeit konzentriert sich auf großflächige Anwendungen von WSNs wie Umwelt- oder Lebensraumüberwachung, die in der Regel den Ad-hoc-Einsatz von Knoten in großen Anzahl erfordern. Ad-hoc-Einsatz und Budgetbeschränkungen hindern Entwickler an der Programmierung der Knoten mit zusätzlichen Informationen wie beispielsweise Routingtabellen, Positionskoordinaten, oder Netzwerkgrenzen. Um diese Informationen zu beschaffen, ist es üblich verschiedene Initialisierungsschemen mit erheblichen Auswirkungen auf den Energieverbrauch und den Programmieraufwand zu implementieren. In Anbetracht dieser Beschränkungen ist ein neues Paradigma für die Initialisierung und den Betrieb von WSNs notwendig, das sich durch einfachen Einsatz und minimalen Energieaufwand auszeichnet. In dieser Arbeit nutzen wir Sink-Mobilität, um den Initialisierungsoverhead und den operativen Overhead zu reduzieren. Unser erster großer Beitrag ist ein Boundary Identification Schema für WSNs mit dem Namen "Mobile Sink based Boundary Detection" (MoSBoD). Es nutzt die Sink-Mobilität um den Kommunikationsoverhead der Sensorknoten zu reduzieren, was zu einer Erhöhung der Laufzeit des WSN führt. Außerdem entstehen durch das Schema keine Einschränkungen in Bezug auf Nodeplacement, Kommunikationsmodell, oder Ortsinformationen der Knoten. Der zweite große Beitrag ist das Congestion avoidance low Latency and Energy efficient (CaLEe) Routingprotokoll für WSNs. CaLEe basiert auf der virtuellen Partitionierung eines Sensorsbereich in Sektoren und der diskreten Mobilität der Sink im WSN. Unsere Simulationsergebnisse zeigen, dass CaLEe, im Vergleich zum derzeitigen State-of-the-art, nicht nur eine erhebliche Reduzierung der durchschnittlichen Energy Dissipation per Node erzielt, sondern auch eine geringere durchschnittliche End-to-End Data Latency in realistischen Szenarien erreicht. Darüber hinaus haben wir festgestellt, dass kein einziges Protokoll in der Lage ist, eine Best-Case-Lösung (minimale Data Latency und minimale Energy Dissipation) für variierende Netzwerkkonfigurationen, die beispielsweise mithilfe der Parameter Kommunikationsbereich der Nodes, Nodedichte, Durchsatz des Sensorfelds definiert werden können, bieten. Daher ist der dritte Hauptbeitrag dieser Arbeit die Identifikation von (auf unterschiedlichen Netzwerkkonfigurationen basierenden) „Operational Regions“, in denen einzelne Protokolle besser arbeiten als andere. Zusammenfassend kann man sagen, dass diese Dissertation das klassische Energieeffizienzproblem der WSNs (Ressource-begrenzte Knoten) aufgreift und gleichzeitig die End-to-End Data Latency auf einen annehmbaren Rahmen eingrenzt.Wireless Sensor Networks (WSN) have gained a considerable attention over the last decade. These networks are characterized by limited amount of energy supply at sensor node. Hence, energy efficiency is an important issue in system design and operation of WSN. This thesis focuses on large-scale applications of WSN, such as environment or habitat monitoring that usually requires ad-hoc deployment of the nodes in large numbers. Ad-hoc deployment and budget constraints restrict developers from programming the nodes with information like routing tables, position coordinates of the node, boundary of the network. In order to acquire this information, state-of-the-art is to program nodes with various initialization schemes that are heavy both from WSN’s (energy consumption) and programmer’s perspectives (programming effort). In view of these particular constraints, we require a new paradigm for WSN initialization and operation, which should be easy to deploy and have minimal energy demands. In this thesis, we exploit sink mobility to reduce the WSN initialization and operational overhead. Our first major contribution is a boundary identification scheme for WSN, named “Mobile Sink based Boundary detection” (MoSBoD). It exploits the sink mobility to remove the communication overhead from the sensor nodes, which leads to an increase in the lifetime of the WSN. Furthermore, it does not impose any restrictions on node placement, communication model, or location information of the nodes. The second major contribution is Congestion avoidance low Latency and Energy efficient (CaLEe) routing protocol for WSN. CaLEe is based on virtual partitioning of a sensor field into sectors and discrete mobility of the sink in the WSN. Our simulation results showed that CaLEe not only achieve considerable reduction in average energy dissipation per node compared to current state-of-the-art routing protocols but also accomplish lesser average end-to-end data latency under realistic scenarios. Furthermore, we observe that no single protocol is capable of providing best-case solution (minium data latency and minimum energy dissipation) under varying network configurations, which can be defined using communication range of the nodes, node density, throughput of the sensor field etc. Therefore, the third major contribution of this thesis is the identification of operational regions (based on varying network configurations) where one protocol performs better than the other. In summary, this thesis revisits the classic energy efficiency problem of a WSN (that have resource-limited nodes) while keeping end-to-end data latency under acceptable bounds

ENAMS: Energy optimization algorithm for mobile wireless sensor networks using evolutionary computation and swarm intelligence.

Although traditionally Wireless Sensor Network (WSNs) have been regarded as static sensor arrays used mainly for environmental monitoring, recently, its applications have undergone a paradigm shift from static to more dynamic environments, where nodes are attached to moving objects, people or animals. Applications that use WSNs in motion are broad, ranging from transport and logistics to animal monitoring, health care and military. These application domains have a number of characteristics that challenge the algorithmic design of WSNs. Firstly, mobility has a negative effect on the quality of the wireless communication and the performance of networking protocols. Nevertheless, it has been shown that mobility can enhance the functionality of the network by exploiting the movement patterns of mobile objects. Secondly, the heterogeneity of devices in a WSN has to be taken into account for increasing the network performance and lifetime. Thirdly, the WSN services should ideally assist the user in an unobtrusive and transparent way. Fourthly, energy-efficiency and scalability are of primary importance to prevent the network performance degradation. This thesis contributes toward the design of a new hybrid optimization algorithm; ENAMS (Energy optimizatioN Algorithm for Mobile Sensor networks) which is based on the Evolutionary Computation and Swarm Intelligence to increase the life time of mobile wireless sensor networks. The presented algorithm is suitable for large scale mobile sensor networks and provides a robust and energy- efficient communication mechanism by dividing the sensor-nodes into clusters, where the number of clusters is not predefined and the sensors within each cluster are not necessary to be distributed in the same density. The presented algorithm enables the sensor nodes to move as swarms within the search space while keeping optimum distances between the sensors. To verify the objectives of the proposed algorithm, the LEGO-NXT MIND-STORMS robots are used to act as particles in a moving swarm keeping the optimum distances while tracking each other within the permitted distance range in the search space

Supporting Management lnteraction and Composition of Self-Managed Cells

Management in ubiquitous systems cannot rely on human intervention or centralised decision-making functions because systems are complex and devices are inherently mobile and cannot refer to centralised management applications for reconfiguration and adaptation directives. Management must be devolved, based on local decision-making and feedback control-loops embedded in autonomous components. Previous work has introduced a Self-Managed Cell (SMC) as an infrastructure for building ubiquitous applications. An SMC consists of a set of hardware and software components that implement a policy-driven feedback control-loop. This allows SMCs to adapt continually to changes in their environment or in their usage requirements. Typical applications include body-area networks for healthcare monitoring, and communities of unmanned autonomous vehicles (UAVs) for surveillance and reconnaissance operations. Ubiquitous applications are typically formed from multiple interacting autonomous components, which establish peer-to-peer collaborations, federate and compose into larger structures. Components must interact to distribute management tasks and to enforce communication strategies. This thesis presents an integrated framework which supports the design and the rapid establishment of policy-based SMC interactions by systematically composing simpler abstractions as building elements of a more complex collaboration. Policy-based interactions are realised – subject to an extensible set of security functions – through the exchanges of interfaces, policies and events, and our framework was designed to support the specification, instantiation and reuse of patterns of interaction that prescribe the manner in which these exchanges are achieved. We have defined a library of patterns that provide reusable abstractions for the structure, task-allocation and communication aspects of an interaction, which can be individually combined for building larger policy-based systems in a methodical manner. We have specified a formal model to ensure the rigorous verification of SMC interactions before policies are deployed in physical devices. A prototype has been implemented that demonstrates the practical feasibility of our framework in constrained resources