技術解説 IEEE Computer

Network Simulator NS2

http://wpage.unina.it/a.botta/pub/COMNET_WORKLOAD.pdf

A tool for the generation of realistic network workload for emerging networking scenarios

This paper describes the design and implementation of a network virtualization substrate (NVS ) for effective virtualization of wireless resources in cellular networks. Virtualization fosters the realization of several interesting deployment scenarios such as customized virtual networks, virtual services, and wide-area corporate networks, with diverse performance objectives. In virtualizing a base station's uplink and downlink resources into slices, \ssr NVS meets three key requirements-isolation, customization, and efficient resource utilization-using two novel features: 1) NVS introduces a provably optimal slice scheduler that allows existence of slices with bandwidth-based and resource-based reservations simultaneously; and 2) NVS includes a generic framework for efficiently enabling customized flow scheduling within the base station on a per-slice basis. Through a prototype implementation and detailed evaluation on a WiMAX testbed, we demonstrate the efficacy of \ssr NVS. For instance, we show for both downlink and uplink directions that \ssr NVS can run different flow schedulers in different slices, run different slices simultaneously with different types of reservations, and perform slice-specific application optimizations for providing customized services.

NVS: a substrate for virtualizing wireless resources in cellular networks

Heterogeneous Internet of Things (HetIoT) is an emerging research field that has strong potential to transform both our understanding of fundamental computer science principles and our future living. HetIoT is being employed in increasing number of areas, such as smart home, smart city, intelligent transportation, environmental monitoring, security systems, and advanced manufacturing. Therefore, relaying on strong application fields, HetIoT will be filled in our life and provide a variety of convenient services for our future. The network architectures of IoT are intrinsically heterogeneous, including wireless sensor network, wireless fidelity network, wireless mesh network, mobile communication network, and vehicular network. In each network unit, smart devices utilize appropriate communication methods to integrate digital information and physical objects, which provide users with new exciting applications and services. However, the complexity of application requirements, the heterogeneity of network architectures and communication technologies impose many challenges in developing robust HetIoT applications. This paper proposes a four-layer HetIoT architecture consisting of sensing, networking, cloud computing, and applications. Then, the state of the art in HetIoT research and applications have been discussed. This paper also suggests several potential solutions to address the challenges facing future HetIoT, including self-organizing, big data transmission, privacy protection, data integration and processing in large-scale HetIoT.

How Can Heterogeneous Internet of Things Build Our Future: A Survey

https://www.nas.ewi.tudelft.nl/people/Piet/papers/ComputerCommunication_QoSR_ENEXT.pdf

Research challenges in QoS routing

The availability of cost-effective wireless network interface cards makes it practical to design network devices with multiple radios which can be exploited to simultane-ously transmit/receive over different frequency channels. It has been shown that using multiple radios per node increases the throughput of multi-hop wireless mesh networks. However, multi-radios create several research challenges. A fundamental problem is the joint channel assignment and routing problem, i.e., how the channels can be assigned to radios and how a set of flow rates can be determined for every network link in order to achieve an anticipated objective. This joint problem is NP-com-plete. Thus, an approximate solution is developed by solving the channel assignment and the routing problems separately. The channel assignment problem turns out to be the problem to assign channels such that a given set of flow rates are schedulable and itself is shown to be also NP-complete. This paper shows that not only the channels but also the transmission rates of the links have to be properly selected to make a given set of flow rates schedulable. Thus, a greedy heuristic for the channel and rate assignment problem is developed. Algorithms to schedule the resulting set of flow rates have been proposed in the literature, which require synchronization among nodes and hence modified coordination functions. Unlike previous work, in this paper a forwarding paradigm is developed to achieve the resulting set of flow rates while using a standard MAC. A bi-dimensional Markov chain model of the proposed forwarding paradigm is presented to analyze its behavior. Thorough performance studies are con-ducted to: a) compare the proposed greedy heuristic to other channel assignment algorithms; b) analyze the behavior of the forwarding paradigm through numerical simulations based on the Markov chain model; c) simulate the operations of the forwarding paradigm and evaluate the achieved network throughput.

A channel and rate assignment algorithm and a layer-2.5 forwarding paradigm for multi-radio wireless mesh networks

A channel assignment algorithm for multi-radio wireless mesh networks

The focus of this paper is on wireless mesh networks. In particular, we study the multi-radio case, given the considerable improvement in network throughput that multiple radios allow to achieve and the availability of cost-effective wireless devices. Interesting research problems are still unsolved in this field. Due to the scarcity of non-overlapped frequency channels and available radios per node, interference is still present, which cuts the achievable throughput down. As interference depends on how channels are bound to radio interfaces, a proper channel assignment scheme is needed to reduce the interference. In this paper we identify some key requirements of a channel assignment scheme. Accordingly, a centralized channel assignment algorithm is developed for multi-radio wireless mesh networks in order to maximize the throughput and address the interference problems. Finally, a performance study is presented to assess the effectiveness of our proposed algorithm.

Stefano Avallone

Papers

Research challenges in QoS routing

A channel and rate assignment algorithm and a layer-2.5 forwarding paradigm for multi-radio wireless mesh networks

A channel assignment algorithm for multi-radio wireless mesh networks

A Channel Assignment Algorithm for Multi-Radio Wireless Mesh Networks

On a fair coexistence of LTE and Wi-Fi in the unlicensed spectrum: A Survey