A hybrid EDA for load balancing in multicast with network coding

Load balancing is one of the most important issues in the practical deployment of multicast with network coding. However, this issue has received little research attention. This paper studies how traffic load of network coding based multicast (NCM) is disseminated in a communications network, with load balancing considered as an important factor. To this end, a hybridized estimation of distribution algorithm (EDA) is proposed, where two novel schemes are integrated into the population based incremental learning (PBIL) framework to strike a balance between exploration and exploitation, thus enhance the efficiency of the stochastic search. The first scheme is a bi-probability-vector coevolution scheme, where two probability vectors (PVs) evolve independently with periodical individual migration. This scheme can diversify the population and improve the global exploration in the search. The second scheme is a local search heuristic. It is based on the problem-specific domain knowledge and improves the NCM transmission plan at the expense of additional computational time. The heuristic can be utilized either as a local search operator to enhance the local exploitation during the evolutionary process, or as a follow-up operator to improve the best-so-far solutions found after the evolution. Experimental results show the effectiveness of the proposed algorithms against a number of existing evolutionary algorithms

QoS constrained cellular ad hoc augmented networks

In this dissertation, based on different design criteria, three novel quality of service (QoS) constrained cellular ad hoc augmented network (CAHAN) architectures are proposed for next generation wireless networks. The CAHAN architectures have a hybrid architecture, in which each MT of CDMA cellular networks has ad hoc communication capability. The CAHAN architectures are an evolutionary approach to conventional cellular networks. The proposed architectures have good system scalability and high system reliability. The first proposed architecture is the QoS constrained minimum-power cellular ad hoc augmented network architecture (QCMP CAHAN). The QCMP CAHAN can find the optimal minimum-power routes under the QoS constraints (bandwidth, packet-delay, or packet-error-rate constraint). The total energy consumed by the MTs is lower in the case of QCMP CAHAN than in the case of pure cellular networks. As the ad hoc communication range of each MT increases, the total transmitted power in QCMP CAHAN decreases. However, due to the increased number of hops involved in information delivery between the source and the destination, the end-to-end delay increases. The maximum end-to-end delay will be limited to a specified tolerable value for different services. An MT in QCMP CAHAN will not relay any messages when its ad hoc communication range is zero, and if this is the case for all MTs, then QCMP CAHAN reduces to the traditional cellular network. A QoS constrained network lifetime extension cellular ad hoc augmented network architecture (QCLE CAHAN) is proposed to achieve the maximum network lifetime under the QoS constraints. The network lifetime is higher in the case of QCLE CAHAN than in the case of pure cellular networks or QCMP CAHAN. In QCLE CAHAN, a novel QoS-constrained network lifetime extension routing algorithm will dynamically select suitable ad-hoc-switch-to-cellular points (ASCPs) according to the MT remaining battery energy such that the selection will balance all the MT battery energy and maximizes the network lifetime. As the number of ASCPs in an ad hoc subnet decreases, the network lifetime will be extended. Maximum network lifetime can be increased until the end-to-end QoS in QCLE CAHAN reaches its maximum tolerable value. Geocasting is the mechanism to multicast messages to the MTs whose locations lie within a given geographic area (target area). Geolocation-aware CAHAN (GA CAHAN) architecture is proposed to improve total transmitted power expended for geocast services in cellular networks. By using GA CAHAN for geocasting, saving in total transmitted energy can be achieved as compared to the case of pure cellular networks. When the size of geocast target area is large, GA CAHAN can save larger transmitted energy

Energy Efficient Downstream Communication in Wireless Sensor Networks

This dissertation studies the problem of energy efficient downstream communication in Wireless Sensor Networks (WSNs). First, we present the Opportunistic Source Routing (OSR), a scalable, reliable, and energy-efficient downward routing protocol for individual node actuation in data collection WSNs. OSR introduces opportunistic routing into traditional source routing based on the parent set of a node’s upward routing in data collection, significantly addressing the drastic link dynamics in low-power and lossy WSNs. We devise a novel adaptive Bloom filter mechanism to effectively and efficiently encode a downward source-route in OSR, which enables a significant reduction of the length of source-route field in the packet header. OSR is scalable to very large-size WSN deployments, since each resource-constrained node in the network stores only the set of its direct children. The probabilistic nature of the Bloom filter passively explores opportunistic routing. Upon a delivery failure at any hop along the downward path, OSR actively performs opportunistic routing to bypass the obsolete/bad link. The evaluations in both simulations and real-world testbed experiments demonstrate that OSR significantly outperforms the existing approaches in scalability, reliability, and energy efficiency. Secondly, we propose a mobile code dissemination tool for heterogeneous WSN deployments operating on low power links. The evaluation in lab experiment and a real world WSN testbed shows how our tool reduces the laborious work to reprogram nodes for updating the application. Finally, we present an empirical study of the network dynamics of an out-door heterogeneous WSN deployment and devise a benchmark data suite. The network dynamics analysis includes link level characteristics, topological characteristics, and temporal characteristics. The unique features of the benchmark data suite include the full path information and our approach to fill the missing paths based on the principle of the routing protocol

Optimizing performance and energy efficiency of group communication and internet of things in cognitive radio networks

Data traffic in the wireless networks has grown at an unprecedented rate. While traditional wireless networks follow fixed spectrum assignment, spectrum scarcity problem becomes a major challenge in the next generations of wireless networks. Cognitive radio is a promising candidate technology that can mitigate this critical challenge by allowing dynamic spectrum access and increasing the spectrum utilization. As users and data traffic demands increases, more efficient communication methods to support communication in general, and group communication in particular, are needed. On the other hand, limited battery for the wireless network device in general makes it a bottleneck for enhancing the performance of wireless networks. In this thesis, the problem of optimizing the performance of group communication in CRNs is studied. Moreover, energy efficient and wireless-powered group communication in CRNs are considered. Additionally, a cognitive mobile base station and a cognitive UAV are proposed for the purpose of optimizing energy transfer and data dissemination, respectively. First, a multi-objective optimization for many-to-many communication in CRNs is considered. Given a many-to-many communication request, the goal is to support message routing from each user in the many-to-many group to each other. The objectives are minimizing the delay and the number of used links and maximizing data rate. The network is modeled using a multi-layer hyper graph, and the secondary users\u27 transmission is scheduled after establishing the conflict graph. Due to the difficulty of solving the problem optimally, a modified version of an Ant Colony meta-heuristic algorithm is employed to solve the problem. Additionally, energy efficient multicast communication in CRNs is introduced while considering directional and omnidirectional antennas. The multicast service is supported such that the total energy consumption of data transmission and channel switching is minimized. The optimization problem is formulated as a Mixed Integer Linear Program (MILP), and a heuristic algorithm is proposed to solve the problem in polynomial time. Second, wireless-powered machine-to-machine multicast communication in cellular networks is studied. To incentivize Internet of Things (IoT) devices to participate in forwarding the multicast messages, each IoT device participates in messages forwarding receives Radio Frequency (RF) energy form Energy Transmitters (ET) not less than the amount of energy used for messages forwarding. The objective is to minimize total transferred energy by the ETs. The problem is formulated mathematically as a Mixed Integer Nonlinear Program (MINLP), and a Generalized Bender Decomposition with Successive Convex Programming (GBD-SCP) algorithm is introduced to get an approximate solution since there is no efficient way in general to solve the problem optimally. Moreover, another algorithm, Constraints Decomposition with SCP and Binary Variable Relaxation (CDR), is proposed to get an approximate solution in a more efficient way. On the other hand, a cognitive mobile station base is proposed to transfer data and energy to a group of IoT devices underlying a primary network. Total energy consumed by the cognitive base station in its mobility, data transmission and energy transfer is minimized. Moreover, the cognitive base station adjusts its location and transmission power and transmission schedule such that data and energy demands are supported within a certain tolerable time and the primary users are protected from harmful interference. Finally, we consider a cognitive Unmanned Aerial Vehicle (UAV) to disseminate data to IoT devices. The UAV senses the spectrum and finds an idle channel, then it predicts when the corresponding primary user of the selected channel becomes active based on the elapsed time of the off period. Accordingly, it starts its transmission at the beginning of the next frame right after finding the channel is idle. Moreover, it decides the number of the consecutive transmission slots that it will use such that the number of interfering slots to the corresponding primary user does not exceed a certain threshold. A mathematical problem is formulated to maximize the minimum number of bits received by the IoT devices. A successive convex programming-based algorithm is used to get a solution for the problem in an efficiency way. It is shown that the used algorithm converges to a Kuhn Tucker point

Bandwidth-aware and energy-efficient stream multicasting protocols for wireless multimedia sensor networks

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 64-66.In recent years, the interest in wireless sensor networks has grown and resulted in the integration of low-power wireless technologies with cameras and microphones enabling video and audio transport through a sensor network besides transporting low-rate environmental measurement-data. These sensor networks are called wireless multimedia sensor networks (WMSN) and are still constrained in terms of battery, memory and achievable data rate. Hence, delivering multimedia content in such an environment has become a new research challenge. Depending on the application, content may need to be delivered to a single destination (unicast) or multiple destinations (multicast). In this work, we consider the problem of e ciently and e ectively delivering a multimedia stream to multiple destinations, i.e. the multimedia multicasting problem, in wireless sensor networks. Existing multicasting solutions for wireless sensor networks provide energy e ciency for low-bandwidth and delay-tolerant data. The aim of this work is to provide a framework that will enable multicasting of relatively highrate and long-durational multimedia streams while trying to meet the desired quality-of-service requirements. To provide the desired bandwidth to a multicast stream, our framework tries to discover, select and use multicasting paths that go through uncongested nodes and in this way have enough bandwidth, while also considering energy e ciency in the sensor network. As part of our framework, we propose a multicasting scheme, with both a centralized and distributed version, that can form energy-e cient multicast trees with enough bandwidth. We evaluated the performance of our proposed scheme via simulations and observed that our scheme can e ectively construct such multicast trees.Yargıçoğlu, BurcuM.S

Network coding for reliable wireless sensor networks

Wireless sensor networks are used in many applications and are now a key element in the increasingly growing Internet of Things. These networks are composed of small nodes including wireless communication modules, and in most of the cases are able to autonomously con gure themselves into networks, to ensure sensed data delivery. As more and more sensor nodes and networks join the Internet of Things, collaboration between geographically distributed systems are expected. Peer to peer overlay networks can assist in the federation of these systems, for them to collaborate. Since participating peers/proxies contribute to storage and processing, there is no burden on speci c servers and bandwidth bottlenecks are avoided. Network coding can be used to improve the performance of wireless sensor networks. The idea is for data from multiple links to be combined at intermediate encoding nodes, before further transmission. This technique proved to have a lot of potential in a wide range of applications. In the particular case of sensor networks, network coding based protocols and algorithms try to achieve a balance between low packet error rate and energy consumption. For network coding based constrained networks to be federated using peer to peer overlays, it is necessary to enable the storage of encoding vectors and coded data by such distributed storage systems. Packets can arrive to the overlay through any gateway/proxy (peers in the overlay), and lost packets can be recovered by the overlay (or client) using original and coded data that has been stored. The decoding process requires a decoding service at the overlay network. Such architecture, which is the focus of this thesis, will allow constrained networks to reduce packet error rate in an energy e cient way, while bene ting from an e ective distributed storage solution for their federation. This will serve as a basis for the proposal of mathematical models and algorithms that determine the most e ective routing trees, for packet forwarding toward sink/gateway nodes, and best amount and placement of encoding nodes.As redes de sensores sem fios são usadas em muitas aplicações e são hoje consideradas um elemento-chave para o desenvolvimento da Internet das Coisas. Compostas por nós de pequena dimensão que incorporam módulos de comunicação sem fios, grande parte destas redes possuem a capacidade de se configurarem de forma autónoma, formando sistemas em rede para garantir a entrega dos dados recolhidos. (…

Smart Sensor Technologies for IoT

The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed. Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications. This Special Issue, “Smart Sensor Technologies for IoT” aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks