Proofs and Performance Evaluation of Greedy Multi-Channel Neighbor Discovery Approaches

The accelerating penetration of physical environments by objects with information processing and wireless communication capabilities requires approaches to find potential communication partners and discover services. In the present work, we focus on passive discovery approaches in multi-channel wireless networks based on overhearing periodic beacon transmissions of neighboring devices which are otherwise agnostic to the discovery process. We propose a family of low-complexity algorithms that generate listening schedules guaranteed to discover all neighbors. The presented approaches simultaneously depending on the beacon periods optimize the worst case discovery time, the mean discovery time, and the mean number of neighbors discovered until any arbitrary in time. The presented algorithms are fully compatible with technologies such as IEEE 802.11 and IEEE 802.15.4. Complementing the proposed low-complexity algorithms, we formulate the problem of computing discovery schedules that minimize the mean discovery time for arbitrary beacon periods as an integer linear problem. We study the performance of the proposed approaches analytically, by means of numerical experiments, and by extensively simulating them under realistic conditions. We observe that the generated listening schedules significantly - by up to factor 4 for the mean discovery time, and by up to 300% for the mean number of neighbors discovered until each point in time - outperform the Passive Scan, a discovery approach defined in the IEEE 802.15.4 standard. Based on the gained insights, we discuss how the selection of the beacon periods influences the efficiency of the discovery process, and provide recommendations for the design of systems and protocols

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

A Comparative Study of Various Routing Protocols in VANET

Vehicular Ad Hoc Networks (VANET) is a subclass of Mobile ad hoc networks which provides a distinguished approach for Intelligent Transport System (ITS). The survey of routing protocols in VANET is important and necessary for smart ITS. This paper discusses the advantages / disadvantages and the applications of various routing protocols for vehicular ad hoc networks. It explores the motivation behind the designed, and traces the evolution of these routing protocols. F inally the paper concludes by a tabular comparison of the various routing protocols for VANET.Comment: 6 pages, 1 figure and 2 table

Settling Payments Fast and Private: Efficient Decentralized Routing for Path-Based Transactions

Path-based transaction (PBT) networks, which settle payments from one user to another via a path of intermediaries, are a growing area of research. They overcome the scalability and privacy issues in cryptocurrencies like Bitcoin and Ethereum by replacing expensive and slow on-chain blockchain operations with inexpensive and fast off-chain transfers. In the form of credit networks such as Ripple and Stellar, they also enable low-price real-time gross settlements across different currencies. For example, SilentWhsipers is a recently proposed fully distributed credit network relying on path-based transactions for secure and in particular private payments without a public ledger. At the core of a decentralized PBT network is a routing algorithm that discovers transaction paths between payer and payee. During the last year, a number of routing algorithms have been proposed. However, the existing ad hoc efforts lack either efficiency or privacy. In this work, we first identify several efficiency concerns in SilentWhsipers. Armed with this knowledge, we design and evaluate SpeedyMurmurs, a novel routing algorithm for decentralized PBT networks using efficient and flexible embedding-based path discovery and on-demand efficient stabilization to handle the dynamics of a PBT network. Our simulation study, based on real-world data from the currently deployed Ripple credit network, indicates that SpeedyMurmurs reduces the overhead of stabilization by up to two orders of magnitude and the overhead of routing a transaction by more than a factor of two. Furthermore, using SpeedyMurmurs maintains at least the same success ratio as decentralized landmark routing, while providing lower delays. Finally, SpeedyMurmurs achieves key privacy goals for routing in PBT networks.Comment: 15 pages, 3 figure

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

User Selection and Power Allocation in Full Duplex Multi-Cell Networks

Full duplex (FD) communications has the potential to double the capacity of a half duplex (HD) system at the link level. However, in a cellular network, FD operation is not a straightforward extension of half duplex operations. The increased interference due to a large number of simultaneous transmissions in FD operation and realtime traffic conditions limits the capacity improvement. Realizing the potential of FD requires careful coordination of resource allocation among the cells as well as within the cell. In this paper, we propose a distributed resource allocation, i.e., joint user selection and power allocation for a FD multi-cell system, assuming FD base stations (BSs) and HD user equipment (UEs). Due to the complexity of finding the globally optimum solution, a sub-optimal solution for UE selection, and a novel geometric programming based solution for power allocation, are proposed. The proposed distributed approach converges quickly and performs almost as well as a centralized solution, but with much lower signaling overhead. It provides a hybrid scheduling policy which allows FD operations whenever it is advantageous, but otherwise defaults to HD operation. We focus on small cell systems because they are more suitable for FD operation, given practical self-interference cancellation limits.With practical self-interference cancellation, it is shown that the proposed hybrid FD system achieves nearly two times throughput improvement for an indoor multi-cell scenario, and about 65% improvement for an outdoor multi-cell scenario compared to the HD system.Comment: 15 pages, to be published in IEEE Transactions on Vehicular Technology, 2016. arXiv admin note: text overlap with arXiv:1412.870

Density-aware Dynamic Mobile Networks: Opportunities and Challenges

We experience a major paradigm change in mobile networks. The infrastructure of cellular networks becomes mobile as it is densified by using mobile and nomadic small cells to increase coverage and capacity. Furthermore, the innovative approaches such as green operation through sleep scheduling, user-controlled small cells, and end-to-end slicing will make the network highly dynamic. Mobile cells, while bringing many benefits, introduce many unconventional challenges that we present in this paper. We have to introduce novel techniques for adapting network functions, communication protocols and their parameters to network density. Especially when cells on wheels or wings are considered, static and man-made configurations will waste valuable resources such as spectrum or energy if density is not considered as an optimization parameter. In this paper, we present the existing density estimators. We analyze the impact of density on coverage, interference, mobility management, scalability, capacity, caching, routing protocols and energy consumption. We evaluate nomadic cells in dynamic networks in a comprehensive way and illustrate the potential objectives we can achieve by adapting mobile networks to base station density. The main challenges we may face by employing dynamic networks and how we can tackle these problems are discussed in detail

Geographic routing protocols for underwater wireless sensor networks:a survey

Underwater wireless sensor networks (UWSN), similar to the terrestrial sensor networks, have different challenges such as limited bandwidth, low battery power, defective underwater channels, and high variable propagation delay. A crucial problem in UWSN is finding an efficient route between a source and a destination. Consequently, great efforts have been made for designing efficient protocols while considering the unique characteristics of underwater communication. Several routing protocols are proposed for this issue and can be classified into geographic and non-geographic routing protocols. In this paper we focus on the geographic routing protocols. We introduce a review and comparison of different algorithms proposed recently in the literature. We also presented a novel taxonomy of these routing in which the protocols are classified into three categories (greedy, restricted directional flooding and hierarchical) according to their forwarding strategies.Comment: 19 pages, IJWMN journa

Exploiting Device-to-Device Communications in Joint Scheduling of Access and Backhaul for mmWave Small Cells

With the explosive growth of mobile data demand, there has been an increasing interest in deploying small cells of higher frequency bands underlying the conventional homogeneous macrocell network, which is usually referred to as heterogeneous cellular networks, to significantly boost the overall network capacity. With vast amounts of spectrum available in the millimeter wave (mmWave) band, small cells at mmWave frequencies are able to provide multi-gigabit access data rates, while the wireless backhaul in the mmWave band is emerging as a cost-effective solution to provide high backhaul capacity to connect access points (APs) of the small cells. In order to operate the mobile network optimally, it is necessary to jointly design the radio access and backhaul networks. Meanwhile, direct transmissions between devices should also be considered to improve system performance and enhance the user experience. In this paper, we propose a joint transmission scheduling scheme for the radio access and backhaul of small cells in the mmWave band, termed D2DMAC, where a path selection criterion is designed to enable device-to-device transmissions for performance improvement. In D2DMAC, a concurrent transmission scheduling algorithm is proposed to fully exploit spatial reuse in mmWave networks. Through extensive simulations under various traffic patterns and user deployments, we demonstrate D2DMAC achieves near-optimal performance in some cases, and outperforms other protocols significantly in terms of delay and throughput. Furthermore, we also analyze the impact of path selection on the performance improvement of D2DMAC under different selected parameters.Comment: 16 pages, 26 figures, a journal paper, Accepted by IEEE JSAC Special Issue on Recent Advances in Heterogeneous Network

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

Bipartite b-matching is fundamental in algorithm design, and has been widely applied into economic markets, labor markets, etc. These practical problems usually exhibit two distinct features: large-scale and dynamic, which requires the matching algorithm to be repeatedly executed at regular intervals. However, existing exact and approximate algorithms usually fail in such settings due to either requiring intolerable running time or too much computation resource. To address this issue, we propose \texttt{NeuSearcher} which leverages the knowledge learned from previously instances to solve new problem instances. Specifically, we design a multichannel graph neural network to predict the threshold of the matched edges weights, by which the search region could be significantly reduced. We further propose a parallel heuristic search algorithm to iteratively improve the solution quality until convergence. Experiments on both open and industrial datasets demonstrate that \texttt{NeuSearcher} can speed up 2 to 3 times while achieving exactly the same matching solution compared with the state-of-the-art approximation approaches.Comment: accepted by IJCAI 202