Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness

Enabling Hardware Green Internet of Things: A review of Substantial Issues

Between now and the near future, the Internet of Things (IoT) will redesign the socio-ecological morphology of the human terrain. The IoT ecosystem deploys diverse sensor platforms connecting millions of heterogeneous objects through the Internet. Irrespective of sensor functionality, most sensors are low energy consumption devices and are designed to transmit sporadically or continuously. However, when we consider the millions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology, as well as the development of EE solutions for sustainable IoT technology, cannot be overemphasised. Propelled by this need, EE proposals are expected to address the EE issues in the IoT context. Consequently, many developments continue to emerge, and the need to highlight them to provide clear insights to researchers on eco-sustainable and green IoT technologies becomes a crucial task. To pursue a clear vision of green IoT, this study aims to present the current state-of-the art insights into energy saving practices and strategies on green IoT. The major contribution of this study includes reviews and discussions of substantial issues in the enabling of hardware green IoT, such as green machine to machine, green wireless sensor networks, green radio frequency identification, green microcontroller units, integrated circuits and processors. This review will contribute significantly towards the future implementation of green and eco-sustainable IoT

The information funnel: Exploiting named data for information-maximizing data collection

Abstract-This paper describes the exploitation of hierarchical data names to achieve information-utility maximizing data collection in social sensing applications. We describe a novel transport abstraction, called the information funnel. It encapsulates a data collection protocol for social sensing that maximizes a measure of delivered information utility, that is the minimized data redundancy, by diversifying the data objects to be collected. The abstraction leverages named-data networking, a communication paradigm where data objects are named instead of hosts. We argue that this paradigm is especially suited for utility-maximizing transport in resource constrained environments, because hierarchical data names give rise to a notion of distance between named objects that is a function of only the topology of the name tree. This distance, in turn, can expose similarities between named objects that can be leveraged for minimizing redundancy among objects transmitted over bottlenecks, thereby maximizing their aggregate utility. With a proper hierarchical name space design, our protocol prioritizes transmission of data objects over bottlenecks to maximize information utility, with very weak assumptions on the utility function. This prioritization is achieved merely by comparing data name prefixes, without knowing application-level name semantics, which makes it generalizable across a wide range of applications. Evaluation results show that the information funnel improves the utility of the collected data objects compared to other lossy protocols

An Energy-Efficient Bit Allocation Scheme in Wireless Sensor Networks

In wireless sensor networks (WSN), a large number of sensor nodes which are capable of sensing, data processing and communicating are densely deployed in an area to measure some physical phenomenon. Generally, wireless sensor nodes carry very limited irreplaceable power sources. Thus, two primary concerns in WSN are to save the overall energy consumption and to prolong the network lifetime, namely the time when all the nodes are functional. Motivated by these two concerns, this thesis mainly focuses on the energy efficient transmission and bit allocation schemes in multi-source single-sink WSN from an information theoretic point of view. Specifically, this thesis investigates the interactions between source coding and channel coding to gain cooperation between them in terms of energy efficiency. For transmission through additive white Gaussian noise (AWGN) channel with path loss, this work shows that the overall energy consumption can be minimized if each source transmits with minimum power and cooperates with other sensors in TDMA (time-division multiple access) mode. From the source coding perspective, the Slepian-Wolf coding theorem is applied for efficient bit allocation since sources are usually highly correlated in WSN. Combining the transmission with correlated source coding, we derive an optimal closed form bit allocation scheme to minimize the overall energy consumption. The fundamental idea is to allocate more bits to the nodes with better channel conditions and less bits to the nodes with worse channel conditions. Based on this scheme, we further maximize the network lifetime and develop a heuristic algorithm to average the distribution of energy consumption among all sensors. Both analytical and simulation results are presented to show the superiority of our schemes

A Novel Communication Approach For Wireless Mobile Smart Objects

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2007Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2007Telsiz ağlar gezgin kullanıcılara nerede olduklarına bağlı olmadan her yerde iletişim kurma ve bilgiye erişim imkanı sağlar. Hiçbir sabit altyapıya gerek duymadan bu imkanı sağlayan tasarsız ağların zaman içinde gelişmesiyle, askeri, ticari ve özel maksatlar için tercih edilir hale gelmiştir. Diğer yandan, bilimsel ve teknolojik gelişmeler ağ elemanlarını daha küçük ve ucuz hale getirdikçe birçok uygulamanın vazgeçilmez parçaları olmuşlardır. Bu ağ elemanları, taşıyıcılara (örneğin gemiler, uçaklar, büyük araçlar, arabalar, insanlar, hayvanlar, vb.) monteli nesneler veya kendi taşıyıcısı olan (aktörler, duyargalar) nesneler olabilir. Fakat bu ağ elemanları ve uygulamalarında bir takım zorluklar yaşanmaktadır. Bu tezde, gezgin tasarsız ve duyarga ağlardaki yaşanan zorlukları ve beklentileri dikkate alarak, gezgin tasarsız ve duyarga ağlar için yeni bir özgün, durumsuz veri akış yaklaşımı ve yönlendirme algoritması önerilmektedir. Durumsuz Ağırlıklı Yönlendirme (DAY, “Stateless Weighted Routing – SWR”) algoritması olarak adlandırdığımız bu algoritma, diğer yöntemlere göre daha az yönlendirme yükü, daha az enerji tüketimi, daha az yol oluşturma gecikmesi sağlamaktadır. Veri, varışa doğru, çoklu yollar üzerinden taşınmaktadır. Çoklu yol oluşturma, güvenirliği sağlamakta, boşluk problemini büyük oranda çözmekte ve en kısa yolu da içeren daha gürbüz yollar oluşmasını sağlamaktadır. DAY aynı zamanda büyük ölçekli ağlarda da uygulanabilir. Bu amaçla, birden fazla veri toplanma düğümü (sink) içeren sürümü olan Çoklu Veri Toplanma Düğümlü- Durumsuz Ağırlıklı Yönlendirme (ÇVTD-DAY - “Multiple Sink-Stateless Weighted Routing - MS-SWR”) yöntemi de büyük ölçekli tasarsız ve duyarga ağları için önerilmiştir. ÇVTD-DAY yöntemi, DAY yönteminde herhangi bir yöntemsel ve algoritmik değişiklik yapmadan birden fazla veri toplanma düğümünün olduğu ağlarda uygulanabilir. Hem DAY, hem ÇVTD-DAY’nin başarımı benzetimler ile ölçüldü. Elde edilen sonuçlar, DAY ‘nin gezgin tasarsız ve duyarga ağlar için istenenleri karşıladığını, karşılaştırılan diğer yöntemlere göre üstün olduğunu ve olası en iyi çözüme yakınlığını, öte yandan ÇVTD-DAY‘nin de büyük ölçekli ağlarda uygulanabilir olduğunu göstermektedir.Wireless networks provide mobile user with ubiquitous communication capability and information access regardless of location. Mobile ad hoc networks, that manage it without a need to infrastructure networks, as evolved in time, become more preferable for military, commercial and special purposes. On the other hand, technological advances made network components smaller and cheaper. These network components involves a wide variety of objects such as objects mounted on crafts/platforms (e.g. ships, aircrafts, trucks, cars, humans, animals), and objects that have their own platforms (e.g. actuators, sensor nodes). However, these network components and their involved applications exhibit some challenges to implement. By considering the challenges and expectations of mobile ad hoc networks and sensor network, we propose a novel stateless data flow approach and routing algorithm namely Stateless Weighted Routing (SWR) for mobile ad hoc and sensor networks. The SWR has low routing overhead providing very low energy consumption, and has low route construction delay than other proposed schemes. Multiple paths to the destination are established for data transmission. Constructing multiple paths provides reliability, eliminates the void problem substantially, and provides more robust routes including the shortest path. The SWR is applicable to large scale networks. We propose the multiple-sink version of the SWR that is namely MS-SWR, to be used in large scale ad hoc and sensor networks with multiple sinks. The MS-SWR can be used with multiple sinks without any functional and algorithmic modification in the SWR protocol. The performance of the SWR and the MS-SWR are evaluated by simulations. The performance of the system shows that the SWR satisfies the requirements of mobile ad hoc networks and outperforms the existing algorithms. The SWR is also tested against a hypothetic routing scheme that finds the shortest available path with no cost in order to compare the performance of the SWR against such an ideal case. Tests also indicate that MS-SWR is scalable for large scale networks.DoktoraPh

A Distributed Framework for Correlated Data Gathering in Sensor Networks

We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation. Second, we would like to find a transmission structure on the network graph such that the total transmission energy consumed by the network is minimized. The existing solutions to this problem are impractical for deployment because they have not considered all of the following factors: 1) distributed implementation; 2) capacity and interference associated with the shared medium; and 3) realistic data correlation model. In this paper, we propose a new distributed framework to achieve minimum energy data gathering while considering these three factors. Based on a localized version of Slepian–Wolf coding, the problem is modeled as an optimization formulation with a distributed solution. The formulation is first relaxed with Lagrangian dualization and then solved with the subgradient algorithm. The algorithm is amenable to fully distributed implementations, which corresponds to the decentralized nature of sensor networks. To evaluate its effectiveness, we have conducted extensive simulations under a variety of network environments. The results indicate that the algorithm supports asynchronous network settings, sink mobility, and duty schedules