Wireless Heterogeneous Networks and Next Generation Internet

The recent advances in wireless access technologies as well as the increasing number of mobile applications have made Wireless Internet a reality. A wide variety of bandwidth demanding services including high speed data delivery and multimedia communication have been materialized through the convergence of the next generation Internet and heterogeneous wireless networks. However, providing even higher bandwidth and richer applications necessitates a fundamental understanding of wireless Internet architecture and the interactions between heterogeneous users. Consequently, fundamental advances in many concepts of the wireless Internet are required for the ultimate goal of communication anytime anywhere. This special issue of the ACM Mobile Networks and Applications Journal is dedicated to the recent advances in the area of Wireless Internet. We accepted 10 papers out of 59 submissions from all over the world with a 17% acceptance rate. Papers describing management schemes, protocols, models, evaluation methods, and experimental studies of Wireless Internet are included in this special issue to provide a broad view of recent advances in this field

A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

JiTS: Just-in-Time Scheduling for Real-Time Sensor Data Dissemination

We consider the problem of real-time data dissemination in wireless sensor networks, in which data are associated with deadlines and it is desired for data to reach the sink(s) by their deadlines. To this end, existing real-time data dissemination work have developed packet scheduling schemes that prioritize packets according to their deadlines. In this paper, we first demonstrate that not only the scheduling discipline but also the routing protocol has a significant impact on the success of real-time sensor data dissemination. We show that the shortest path routing using the minimum number of hops leads to considerably better performance than Geographical Forwarding, which has often been used in existing real-time data dissemination work. We also observe that packet prioritization by itself is not enough for real-time data dissemination, since many high priority packets may simultaneously contend for network resources, deteriorating the network performance. Instead, real-time packets could be judiciously delayed to avoid severe contention as long as their deadlines can be met. Based on this observation, we propose a Just-in-Time Scheduling (JiTS) algorithm for scheduling data transmissions to alleviate the shortcomings of the existing solutions. We explore several policies for non-uniformly delaying data at different intermediate nodes to account for the higher expected contention as the packet gets closer to the sink(s). By an extensive simulation study, we demonstrate that JiTS can significantly improve the deadline miss ratio and packet drop ratio compared to existing approaches in various situations. Notably, JiTS improves the performance requiring neither lower layer support nor synchronization among the sensor nodes

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Smartening the Environment using Wireless Sensor Networks in a Developing Country

The miniaturization process of various sensing devices has become a reality by enormous research and advancements accomplished in Micro Electro-Mechanical Systems (MEMS) and Very Large Scale Integration (VLSI) lithography. Regardless of such extensive efforts in optimizing the hardware, algorithm, and protocols for networking, there still remains a lot of scope to explore how these innovations can all be tied together to design Wireless Sensor Networks (WSN) for smartening the surrounding environment for some practical purposes. In this paper we explore the prospects of wireless sensor networks and propose a design level framework for developing a smart environment using WSNs, which could be beneficial for a developing country like Bangladesh. In connection to this, we also discuss the major aspects of wireless sensor networks.Comment: 5 page

On the design of an energy-efficient low-latency integrated protocol for distributed mobile sensor networks

Self organizing, wireless sensors networks are an emergent and challenging technology that is attracting large attention in the sensing and monitoring community. Impressive progress has been done in recent years even if we need to assume that an optimal protocol for every kind of sensor network applications can not exist. As a result it is necessary to optimize the protocol for certain scenarios. In many applications for instance latency is a crucial factor in addition to energy consumption. MERLIN performs its best in such WSNs where there is the need to reduce the latency while ensuring that energy consumption is kept to a minimum. By means of that, the low latency characteristic of MERLIN can be used as a trade off to extend node lifetimes. The performance in terms of energy consumption and latency is optimized by acting on the slot length. MERLIN is designed specifically to integrate routing, MAC and localization protocols together. Furthermore it can support data queries which is a typical application for WSNs. The MERLIN protocol eliminates the necessity to have any explicit handshake mechanism among nodes. Furthermore, the reliability is improved using multiple path message propagation in combination with an overhearing mechanism. The protocol divides the network into subsets where nodes are grouped in time zones. As a result MERLIN also shows a good scalability by utilizing an appropriate scheduling mechanism in combination with a contention period