Low-Complexity Energy-Efficient Broadcasting in One-Dimensional Wireless Networks

In this paper, we investigate the transmission range assignment for N wireless nodes located on a line (a linear wireless network) for broadcasting data from one specific node to all the nodes in the network with minimum energy. Our goal is to find a solution that has low complexity and yet performs close to optimal. We propose an algorithm for finding the optimal assignment (which results in the minimum energy consumption) with complexity O(N^2). An approximation algorithm with complexity O(N) is also proposed. It is shown that, for networks with uniformly distributed nodes, the linear-time approximate solution obtained by this algorithm on average performs practically identical to the optimal assignment. Both the optimal and the suboptimal algorithms require the full knowledge of the network topology and are thus centralized. We also propose a distributed algorithm of negligible complexity, i.e., with complexity O(1), which only requires the knowledge of the adjacent neighbors at each wireless node. Our simulations demonstrate that the distributed solution on average performs almost as good as the optimal one for networks with uniformly distributed nodes.Comment: 17 page

High-Performance Broadcast and Multicast Protocols for Multi-Radio Multi-Channel Wireless Mesh Networks

Recently, wireless mesh networks (WMNs) have attracted much attention. A vast amount of unicast, multicast and broadcast protocols has been developed for WMNs or mobile ad hoc networks (MANETs). First of all, broadcast and multicast in wireless networks are fundamentally different from the way in which wired networks function due to the well-known wireless broadcast/multicast advantage. Moreover, most broadcast and multicast protocols in wireless networks assume a single-radio single-channel and single-rate network model, or a generalized physical model, which does not take into account the impact of interference. This dissertation focuses on high-performance broadcast and multicast protocols designed for multi-radio multi-channel (MRMC) WMNs. MRMC increases the capacity of the network from different aspects. Multi-radio allows mesh nodes to simultaneously send and receive through different radios to its neighbors. Multi-channel allows channels to be reused across the network, which expands the available spectrum and reduces the interference. Unlike MANETs, WMNs are assumed to be static or with minimal mobility. Therefore, the main design goal in WMNs is to achieve high throughput rather than to maintain connectivity. The capacity of WMNs is constrained by the interference caused by the neighbor nodes. One direct design objective is to minimize or reduce the interference in broadcast and multicast. This dissertation presents a set of broadcast and multicast protocols and mathematical formulations to achieve the design goal in MRMC WMNs. First, the broadcast problem is addressed with full consideration of both inter-node and intra-node interference to achieve efficient broadcast. The interference-aware broadcast protocol simultaneously achieves full reliability, minimum broadcast or multicast latency, minimum redundant transmissions, and high throughput. With an MRMC WMN model, new link and channel quality metrics are defined and are suitable for the design of broadcast and multicast protocols. Second, the minimum cost broadcast problem (MCBP), or minimum number of transmissions problem, is studied for MRMC WMNs. Minimum cost broadcast potentially allows more effective and efficient schedule algorithms to be designed. The proposed protocol with joint consideration of channel assignment reduces the interference to improve the throughput in the MCBP. Minimum cost broadcast in MRMC WMNs is very different from that in the single radio single channel scenario. The channel assignment in MRMC WMNs is used to assign multiple radios of every node to different channels. It determines the actual network connectivity since adjacent nodes have to be assigned to a common channel. Transmission on different channels makes different groups of neighboring nodes, and leads to different interference. Moreover, the selection of channels by the forward nodes impacts on the number of radios needed for broadcasting. Finally, the interference optimization multicast problem in WMNs with directional antennas is discussed. Directional transmissions can greatly reduce radio interference and increase spatial reuse. The interference with directional transmissions is defined for multicast algorithm design. Multicast routing found by the interference-aware algorithm tends to have fewer channel collisions. The research work presented in this dissertation concludes that (1) new and practical link and channel metrics are required for designing broadcast and multicast in MRMC WMNs; (2) a small number of radios is sufficient to significantly improve throughput of broadcast and multicast in WMNs; (3) the number of channels has more impact on almost all performance metrics, such as the throughput, the number of transmission, and interference, in WMNs

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Physical Layer Service Integration in 5G: Potentials and Challenges

High transmission rate and secure communication have been identified as the key targets that need to be effectively addressed by fifth generation (5G) wireless systems. In this context, the concept of physical-layer security becomes attractive, as it can establish perfect security using only the characteristics of wireless medium. Nonetheless, to further increase the spectral efficiency, an emerging concept, termed physical-layer service integration (PHY-SI), has been recognized as an effective means. Its basic idea is to combine multiple coexisting services, i.e., multicast/broadcast service and confidential service, into one integral service for one-time transmission at the transmitter side. This article first provides a tutorial on typical PHY-SI models. Furthermore, we propose some state-of-the-art solutions to improve the overall performance of PHY-SI in certain important communication scenarios. In particular, we highlight the extension of several concepts borrowed from conventional single-service communications, such as artificial noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These techniques are shown to be effective in the design of reliable and robust PHY-SI schemes. Finally, several potential research directions are identified for future work.Comment: 12 pages, 7 figure

Energy Complexity of Distance Computation in Multi-hop Networks

Energy efficiency is a critical issue for wireless devices operated under stringent power constraint (e.g., battery). Following prior works, we measure the energy cost of a device by its transceiver usage, and define the energy complexity of an algorithm as the maximum number of time slots a device transmits or listens, over all devices. In a recent paper of Chang et al. (PODC 2018), it was shown that broadcasting in a multi-hop network of unknown topology can be done in $\text{poly} \log n$ energy. In this paper, we continue this line of research, and investigate the energy complexity of other fundamental graph problems in multi-hop networks. Our results are summarized as follows. 1. To avoid spending $\Omega(D)$ energy, the broadcasting protocols of Chang et al. (PODC 2018) do not send the message along a BFS tree, and it is open whether BFS could be computed in $o(D)$ energy, for sufficiently large $D$. In this paper we devise an algorithm that attains $\tilde{O}(\sqrt{n})$ energy cost. 2. We show that the framework of the ${\Omega}(n)$ round lower bound proof for computing diameter in CONGEST of Abboud et al. (DISC 2017) can be adapted to give an $\tilde{\Omega}(n)$ energy lower bound in the wireless network model (with no message size constraint), and this lower bound applies to $O(\log n)$-arboricity graphs. From the upper bound side, we show that the energy complexity of $\tilde{O}(\sqrt{n})$ can be attained for bounded-genus graphs (which includes planar graphs). 3. Our upper bounds for computing diameter can be extended to other graph problems. We show that exact global minimum cut or approximate $s$--$t$ minimum cut can be computed in $\tilde{O}(\sqrt{n})$ energy for bounded-genus graphs

Networking - A Statistical Physics Perspective

Efficient networking has a substantial economic and societal impact in a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption require new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with non-linear large scale systems. This paper aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.Comment: (Review article) 71 pages, 14 figure