Virtual Communication Stack: Towards Building Integrated Simulator of Mobile Ad Hoc Network-based Infrastructure for Disaster Response Scenarios

Responses to disastrous events are a challenging problem, because of possible damages on communication infrastructures. For instance, after a natural disaster, infrastructures might be entirely destroyed. Different network paradigms were proposed in the literature in order to deploy adhoc network, and allow dealing with the lack of communications. However, all these solutions focus only on the performance of the network itself, without taking into account the specificities and heterogeneity of the components which use it. This comes from the difficulty to integrate models with different levels of abstraction. Consequently, verification and validation of adhoc protocols cannot guarantee that the different systems will work as expected in operational conditions. However, the DEVS theory provides some mechanisms to allow integration of models with different natures. This paper proposes an integrated simulation architecture based on DEVS which improves the accuracy of ad hoc infrastructure simulators in the case of disaster response scenarios.Comment: Preprint. Unpublishe

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Trustworthy applications for vehicular environments

The integration of ICT in vehicular environments enables new kinds of application and creates new technological challenges. Dynamic network topology, unreliable network links, and moving terminals make it hard to provide a convincing end user experience. This article introduces the concept of providing trustworthy applications through wireless networks in vehicular environments. A special emphasis will be on how to maintain end users privacy when providing personalized, contextaware services. Therefore, a service taxonomy, enabling middleware technologies, and service enablers are introduced

Using Machine Learning for Handover Optimization in Vehicular Fog Computing

Smart mobility management would be an important prerequisite for future fog computing systems. In this research, we propose a learning-based handover optimization for the Internet of Vehicles that would assist the smooth transition of device connections and offloaded tasks between fog nodes. To accomplish this, we make use of machine learning algorithms to learn from vehicle interactions with fog nodes. Our approach uses a three-layer feed-forward neural network to predict the correct fog node at a given location and time with 99.2 % accuracy on a test set. We also implement a dual stacked recurrent neural network (RNN) with long short-term memory (LSTM) cells capable of learning the latency, or cost, associated with these service requests. We create a simulation in JAMScript using a dataset of real-world vehicle movements to create a dataset to train these networks. We further propose the use of this predictive system in a smarter request routing mechanism to minimize the service interruption during handovers between fog nodes and to anticipate areas of low coverage through a series of experiments and test the models' performance on a test set

An Innovative Technique to Avoid Traffic Jamming for VANET Using NS-2

A range of efficient control of vehicles has grown together with information and communication tools In scrupulous, with the appliance of wireless network for real world information offering, it has been feasible to create Vehicular Ad-hoc Network (VANET), an intellectual vehicle service for ease and protection, which does feasible crash accident detection and prevention, caution of hazardous aspects on road, traffic information offering, and other types of service offering. Nevertheless, the VANET service situation has physical and technical vulnerabilities sourced by the vehicular inside/outside communication based on wireless network. Thus, Vehicular protection has become known as a crucial aspect to avert malevolent threats and confidentiality defiance from vehicles, drivers, and traffic network. In this paper we proposed a scheme for discovering the routing mischief of an attacker aligned with traffic jamming. Now if the congestions take place in a particular section then in that case all vehicular nodes would produce the traffic jam indications known as Jamming declaration indications to their fellow vehicles and through that the vehicular node would modify their direction. Performances of outcomes are calculated on the basis of parameters: Packet Delivery Ratio, Routing Load and Throughput using Network Simulator (NS-2). Keywords: VANET (Vehicular Ad-hoc Network), Vehicle security, traffic jamming, Road Side Uni