The Experts below are selected from a list of 16908 Experts worldwide ranked by ideXlab platform
Eytan Modiano - One of the best experts on this subject based on the ideXlab platform.
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distributed throughput maximization in wireless mesh networks via pre partitioning
IEEE ACM Transactions on Networking, 2008Co-Authors: Andrew Brzezinski, Gil Zussman, Eytan ModianoAbstract:This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multi-Radio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, we present a novel approach that takes advantage of the inherent multi-Radio Capability of WMNs. We show that this Capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of centralized channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms pre-partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. We evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region. We note that while the identified topologies are of general interference graphs, the partitioning algorithms are designed for networks with primary interference constraints.
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enabling distributed throughput maximization in wireless mesh networks a partitioning approach
ACM IEEE International Conference on Mobile Computing and Networking, 2006Co-Authors: Andrew Brzezinski, Gil Zussman, Eytan ModianoAbstract:This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multiRadio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, in this paper we present a novel approach that takes advantage of the inherent multi-Radio Capability of WMNs. We show that this Capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the recently introduced notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. Finally, we evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region.
Andrew Brzezinski - One of the best experts on this subject based on the ideXlab platform.
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distributed throughput maximization in wireless mesh networks via pre partitioning
IEEE ACM Transactions on Networking, 2008Co-Authors: Andrew Brzezinski, Gil Zussman, Eytan ModianoAbstract:This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multi-Radio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, we present a novel approach that takes advantage of the inherent multi-Radio Capability of WMNs. We show that this Capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of centralized channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms pre-partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. We evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region. We note that while the identified topologies are of general interference graphs, the partitioning algorithms are designed for networks with primary interference constraints.
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enabling distributed throughput maximization in wireless mesh networks a partitioning approach
ACM IEEE International Conference on Mobile Computing and Networking, 2006Co-Authors: Andrew Brzezinski, Gil Zussman, Eytan ModianoAbstract:This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multiRadio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, in this paper we present a novel approach that takes advantage of the inherent multi-Radio Capability of WMNs. We show that this Capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the recently introduced notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. Finally, we evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region.
Abderrezak Rachedi - One of the best experts on this subject based on the ideXlab platform.
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cognitive Radio based internet of things applications architectures spectrum related functionalities and future research directions
IEEE Wireless Communications, 2017Co-Authors: Athar Ali Khan, Mubashir Husain Rehmani, Abderrezak RachediAbstract:Recent research and technology trends are shifting toward IoT and CRNs. However, we think that the things-oriented, Internet-oriented, and semantic-oriented versions of IoT are meaningless if IoT objects are not equipped with cognitive Radio Capability. Equipping IoT objects with CR Capability has lead to a new research dimension of CR-based IoT. In this article, we present an overview of CR-based IoT systems. We highlight potential applications of CR-based IoT systems. We survey architectures and frameworks of CR-based IoT systems. We furthermore discuss spectrum-related functionalities for CR-based IoT systems. Finally, we present open issues, research challenges, and future direction for these CR-based IoT networks.
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channel bonding in cognitive Radio wireless sensor networks
International Conference on Smart Homes and Health Telematics, 2012Co-Authors: Mubashir Husain Rehmani, Stephane Lohier, Abderrezak RachediAbstract:Recently, wireless sensor networks are gaining a lot of attention due to the availability of various low cost sensor devices. For example, Wireless Multimedia Sensor Networks (WMSNs) have lot of new potential applications in different domains including, environmental monitoring, home automation, tracking, health care, just to name a few. Another example is the Body Area Networks (BANs), where different sensors are attached with the patient's body. However, these sensor networks also bring several challenges, such as they are resource constraint, requires application specific QoS requirements, high bandwidth demands, and resistance to interference. In this paper, we argue that wireless sensor nodes with cognitive Radio Capability, together with channel bonding, can help to address these challenges. In this perspective, we discuss cognitive Radio wireless sensor network for hospital environment as a case study. We then discuss the way of spectrum characterization and criteria for channel bonding in such networks. Finally, we highlight issues and challenges, which provides the basis to develop algorithms and protocols for the future cognitive Radio wireless sensor network deployments in different application scenarios.
Yingshu Li - One of the best experts on this subject based on the ideXlab platform.
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data aggregation scheduling in probabilistic wireless networks with cognitive Radio Capability
Global Communications Conference, 2016Co-Authors: Chunyu Ai, Yingshu LiAbstract:Transitional Region Phenomenon leads to the existence of lossy links in wireless networks, which results in a transmission between two users who are theoretically connected under the Deterministic Network Model cannot be guaranteed. Therefore, we focus on a more practical network model - Probabilistic Network Model (PNM) which can better characterize the lossy links in wireless networks. To be specific, we focus on the investigation of accelerating data aggregation process in probabilistic wireless networks with the cognitive Radio technology. By involving cognitive Radio technology, users in the wireless networks can seek extra transmission opportunity if other spectrum resource is available. Otherwise, the data aggregation process still can be done on the default working spectrum. Particularly, we are interested in the time efficient data aggregation scheduling problem. In this work, a two phase scheduling algorithm is proposed. The first phase is finding an efficient routing structure considering the speciality of the network model under investigation. In the second phase, a dynamic scheduling algorithm is introduced. Theoretical analysis is provided to estimate the lower latency bound for the scheduling algorithm, followed by the experimental simulation verification.
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data aggregation scheduling in wireless networks with cognitive Radio Capability
Sensor Mesh and Ad Hoc Communications and Networks, 2014Co-Authors: Shouling Ji, Yingshu LiAbstract:Complicated collisions and spectrum uncertainty con- strain the usage of Cognitive Radio Networks (CRNs) on heavy transmission and time sensitive applications. On the other hand, data aggregation has been considered as an essential operation in wireless networks. A large amount of effort has been dedicated to the investigation of CRNs and data aggregation in wireless networks. However, the existing literatures rarely concentrate on how to use cognitive Radio technique to promote the performance of data aggregation in conventional wireless networks. In this paper, we investigate the Minimum Latency Data Aggregation Scheduling in wireless networks with Cognitive Radio capabil- ity (MLDAS-CR) problem. As the first try, an approximation scheduling algorithm based on Integer Linear Programming (ILP) and Linear Programming (LP) is proposed. According to the simulation results, this method performances great, however, it is difficult to theoretically evaluate the solution. Therefore, a heuristic scheduling algorithm with guaranteed latency bound is presented in our further investigation. The performance of the proposed solutions are evaluated through extensive simulations.
Jingping Bi - One of the best experts on this subject based on the ideXlab platform.
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big data routing in d2d communications with cognitive Radio Capability
IEEE Wireless Communications, 2016Co-Authors: Jianhui Huang, Xiuzhen Cheng, Shengling Wang, Jingping BiAbstract:In D2D communications, random contacts can be utilized to exchange data among nodes without the support from infrastructures or central control units. Because of the huge quantity and high mobility of the nodes, the scarcity of the available spectrum severely limits the data delivery capacity in D2D communications. CR technology gives D2D the ability to use idle licensed Radio spectra from licensed networks to improve data delivery capacity. The advantages of opportunistic data delivery and CR technology make D2D communications an alternative that provides a complementary technology for big data applications. However, efficient routing algorithm design in D2D communications with CRD2D is nontrivial due to the spatial, temporal, and spectrum limitations introduced by node mobility and the available spectrum bands. This article investigates and analyzes the latest routing algorithms for D2D communications and CR networks. Taking advantage of the integration of D2D and CR techniques, a routing framework with social awareness for big data applications is proposed, which employs the regularities of nodes' mobility and spectrum mobility to improve the performance of data delivery. Open research issues for big data routing in CRD2D networks are also addressed.
