From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey

Context data is in demand more than ever with the rapid increase in the development of many context-aware Internet of Things applications. Research in context and context-awareness is being conducted to broaden its applicability in light of many practical and technical challenges. One of the challenges is improving performance when responding to large number of context queries. Context Management Platforms that infer and deliver context to applications measure this problem using Quality of Service (QoS) parameters. Although caching is a proven way to improve QoS, transiency of context and features such as variability, heterogeneity of context queries pose an additional real-time cost management problem. This paper presents a critical survey of state-of-the-art in adaptive data caching with the objective of developing a body of knowledge in cost- and performance-efficient adaptive caching strategies. We comprehensively survey a large number of research publications and evaluate, compare, and contrast different techniques, policies, approaches, and schemes in adaptive caching. Our critical analysis is motivated by the focus on adaptively caching context as a core research problem. A formal definition for adaptive context caching is then proposed, followed by identified features and requirements of a well-designed, objective optimal adaptive context caching strategy.Comment: This paper is currently under review with ACM Computing Surveys Journal at this time of publishing in arxiv.or

A Search Strategy of Level-Based Flooding for the Internet of Things

This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales

An Application of Path Sharing To Routing For Mobile Sinks In Wireless Sensor Networks

Power Conservation is one of the most important challenges in wireless sensor networks. In this paper, we present a minimum-energy routing algorithm. Our main goal is to reduce power consumed and prolong the lifespan of the network. The rotocol, named CODEXT: Coordinationbased Data dissemination for Sensor Networks eXTension, addresses the sensor networks consisting of mobile sinks. CODEXT which is an improvement over CODE protocol Coordination-based Data dissemination for sensor networks considers energy conservation not only in communication but also in idle-to-sleep state. Better informed routing decisions can often be made by sharing information among neighbouring nodes. To this end, we describe the CODEXT protocol, a generic outline for Wireless Sensor Network (WSN) protocols that focuses on locally sharing feedback with little or no overhead. This paper describes one instantiation of it, CODEXT protocol for optimizing routing to multiple sinks through reinforcement learning. Such a routing situation arises in WSNs with multiple, possibly mobile sinks, such as WSNs with actuators deployed in parallel to sensors. This protocol is based on GAF protocol and grid structure to reduce energy consumed. Our simulation results show that CODEXT gain energy efficiency and prolong the network lifetime. Keywords: Source, Sink, Coordination-based Data dissemination protocol, WSN

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

Routing Protocols in Wireless Sensor Networks

The applications of wireless sensor networks comprise a wide variety of scenarios. In most of them, the network is composed of a significant number of nodes deployed in an extensive area in which not all nodes are directly connected. Then, the data exchange is supported by multihop communications. Routing protocols are in charge of discovering and maintaining the routes in the network. However, the appropriateness of a particular routing protocol mainly depends on the capabilities of the nodes and on the application requirements. This paper presents a review of the main routing protocols proposed for wireless sensor networks. Additionally, the paper includes the efforts carried out by Spanish universities on developing optimization techniques in the area of routing protocols for wireless sensor networks

Adaptive and context-aware service discovery for the Internet of Things

The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which offer hosted functionality as services. The role of service discovery is crucial when providing application-level, end-to-end integration. In this paper, we propose trendy: a RESTful web services based Service Discovery protocol to tackle the challenges posed by constrained domains while offering the required interoperability. It provides a service selection technique to offer the appropriate service to the user application depending on the available context information of user and services. Furthermore, it employs a demand-based adaptive timer and caching mechanism to reduce the communication overhead and to decrease the service invocation delay. trendy’s grouping technique creates location-based teams of nodes to offer service composition. Our simulation results show that the employed techniques reduce the control packet overhead, service invocation delay and energy consumption. In addition, the grouping technique provides the foundation for group-based service mash-ups and localises control traffic to improve scalability