Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Naming and Address Resolution in Heterogeneous Mobile Ad hoc Networks

This doctoral thesis deals with naming and address resolution in heterogeneous networks to be used in disaster scenarios. Such events could damage the communication infrastructure in parts or completely. To reestablish communication, Mobile Ad hoc Networks (MANETs) could be used where central entities have to be eliminated broadly. The main focus of the thesis lies on two things: an addressing scheme that helps to find nodes, even if they frequently change the subnet and the local addressing, by introducing an identifying name layer; and a MANET-adapted substitution of the Domain Name System (DNS) in order to resolve node identities to changing local addresses. We present our solution to provide decentralized name resolution based on different underlying routing protocols embedded into an adaptive routing framework. Furthermore, we show how this system works in cascaded networks and how to extend the basic approach to realize location-aware service discovery.Auch im Buchhandel erhältlich: Naming and Address Resolution in Heterogeneous Mobile Ad hoc Networks / Sebastian Schellenberg Ilmenau : Univ.-Verl. Ilmenau, 2016. - xvi, 177 Seiten ISBN 978-3-86360-129-4 Preis (Druckausgabe): 17,60

A Case for Time Slotted Channel Hopping for ICN in the IoT

Recent proposals to simplify the operation of the IoT include the use of Information Centric Networking (ICN) paradigms. While this is promising, several challenges remain. In this paper, our core contributions (a) leverage ICN communication patterns to dynamically optimize the use of TSCH (Time Slotted Channel Hopping), a wireless link layer technology increasingly popular in the IoT, and (b) make IoT-style routing adaptive to names, resources, and traffic patterns throughout the network--both without cross-layering. Through a series of experiments on the FIT IoT-LAB interconnecting typical IoT hardware, we find that our approach is fully robust against wireless interference, and almost halves the energy consumed for transmission when compared to CSMA. Most importantly, our adaptive scheduling prevents the time-slotted MAC layer from sacrificing throughput and delay

Survey And New Approach In Service Discovery And Advertisement For Mobile Ad Hoc Networks.

Service advertisement and discovery is an important component for mobile adhoc communications and collaboration in ubiquitous computing environments. The ability to discover services offered in a mobile adhoc network is the major prerequisite for effective usability of these networks. This paper aims to classify and compare existing Service Discovery (SD) protocols for MANETs by grouping them based on their SD strategies and service information accumulation strategies, and to propose an efficient approach for addressing the inherent issues

MoMo: a group mobility model for future generation mobile wireless networks

Existing group mobility models were not designed to meet the requirements for accurate simulation of current and future short distance wireless networks scenarios, that need, in particular, accurate, up-to-date informa- tion on the position of each node in the network, combined with a simple and flexible approach to group mobility modeling. A new model for group mobility in wireless networks, named MoMo, is proposed in this paper, based on the combination of a memory-based individual mobility model with a flexible group behavior model. MoMo is capable of accurately describing all mobility scenarios, from individual mobility, in which nodes move inde- pendently one from the other, to tight group mobility, where mobility patterns of different nodes are strictly correlated. A new set of intrinsic properties for a mobility model is proposed and adopted in the analysis and comparison of MoMo with existing models. Next, MoMo is compared with existing group mobility models in a typical 5G network scenario, in which a set of mobile nodes cooperate in the realization of a distributed MIMO link. Results show that MoMo leads to accurate, robust and flexible modeling of mobility of groups of nodes in discrete event simulators, making it suitable for the performance evaluation of networking protocols and resource allocation algorithms in the wide range of network scenarios expected to characterize 5G networks.Comment: 25 pages, 17 figure