Modeling and Analysis of Emergency Messaging Delay in Vehicular Ad Hoc Networks

Road crashes, occurring at a high annual rate for many years, demand improvements in transportation systems to provide a high level of on-road safety. Implanting smart sensors, communication capabilities, memory storage and information processing units in vehicles are important components of Intelligent Transportation Systems (ITS). ITS should enable the communication between vehicles and allow cooperative driving and early warnings of sudden breaks and accidents ahead. The prompt availability of the emergency information will provide the driver a time to react in order to avoid possible accidents ahead. Hence, information delivery delay is an importance quality-of-service (QoS) metric in such applications. In this thesis, we focus on modeling the delay for emergency messaging in vehicular ad hoc networks (VANETs). VANETs consist of nodes moving with very high speeds, resulting in frequent topological changes. As a result, many existing models and packet forwarding schemes designed for general purpose mobile ad hoc networks (MANETs) cannot be directly applied to VANETs. In our system model, we consider mobility and traffic density of vehicles. We focus on studying the effect of the traffic flow density on the delay of emergency message dissemination. Hence, traffic flow theories developed by civil engineers form the base of our modeling. The common way of emergency message dissemination in VANETs is broadcasting. To overcome the broadcasting storm problem and improve scalability of such large networks, we adopt a node cluster based broadcasting mechanism. This research provides a realistic mathematical model for the broadcasting delay, which accounts for the randomness in user mobility and matches the highly dynamic nature of VANETs. An investigation on the minimum cluster size that achieves acceptable message delivery latency is provided. It is shown that network control and performance parameters are dependent on the traffic density. Experimental measurement data are used to demonstrate the accuracy of the mathematical modeling

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201