A survey on interactive games over mobile networks

open4noThe mobile revolution has brought us the possibility to enjoy our favorite applications anywhere and anytime. In this context, interactive games over mobile networks embody a fascinating case study both for their commercial success and for their technical challenges, thus, sparking interest and development. The current state of the art of interactive games over mobile networks is captured in this article. We discuss main requirements and analyze possible combinations of existing solutions to provide better support for highly interactive game sessions with mobile players.This work has been partially supported by the UniPD Web Squared and MIUR/PRIN ALTER_NET projects.openGerla, M.; Maggiorini, D.; Palazzi, C.E.; Bujari, A.Gerla, M.; Maggiorini, D.; Palazzi, C.E.; Bujari, A

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

Load Balancing in Distributed Cloud Computing: A Reinforcement Learning Algorithms in Heterogeneous Environment

Balancing load in cloud based is an important aspect that plays a vital role in order to achieve sharing of load between different types of resources such as virtual machines that lay on servers, storage in the form of hard drives and servers. Reinforcement learning approaches can be adopted with cloud computing to achieve quality of service factors such as minimized cost and response time, increased throughput, fault tolerance and utilization of all available resources in the network, thus increasing system performance. Reinforcement Learning based approaches result in making effective resource utilization by selecting the best suitable processor for task execution with minimum makespan. Since in the earlier related work done on sharing of load, there are limited reinforcement learning based approaches. However this paper, focuses on the importance of RL based approaches for achieving balanced load in the area of distributed cloud computing. A Reinforcement Learning framework is proposed and implemented for execution of tasks in heterogeneous environments, particularly, Least Load Balancing (LLB) and Booster Reinforcement Controller (BRC) Load Balancing. With the help of reinforcement learning approaches an optimal result is achieved for load sharing and task allocation. In this RL based framework processor workload is taken as an input. In this paper, the results of proposed RL based approaches have been evaluated for cost and makespan and are compared with existing load balancing techniques for task execution and resource utilization.

Towards reliable geographic broadcasting in vehicular networks

In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly

Real time collision warning system in the context of vehicle-to-vehicle data exchange based on drivings behaviours analysis

Worldwide injuries in vehicle accidents have been on the rise in recent years, mainly due to driver error regardless of technological innovations and advancements for vehicle safety. Consequently, there is a need for a reliable-real time warning system that can alert drivers of a potential collision. Vehicle-to-Vehicle (V2V) is an extensive area of ongoing research and development which has started to revolutionize the driving experience. Driving behaviour is a subject of extensive research which gains special attention due to the relationship between speeding behaviour and crashes as drivers who engage in frequent and extreme speeding behaviour are overinvolved in crashes. National Highway Traffic Safety Administration (NHTSA) set guidelines on how different vehicle automation levels may reduce vehicle crashes and how the use of on-board short-range sensors coupled with V2V technologies can help facilitate communication among vehicles. Based on the previous works, it can be seen that the assessment of drivers’ behaviours using their trajectory data is a fresh and open research field. Most studies related to driving behaviours in terms of acceleration�deceleration are evaluated at the laboratory scale using experimental results from actual vehicles. Towards this end, a five-stage methodology for a new collision warning system in the context of V2V based on driving behaviours has been designed. Real-time V2V hardware for data collection purposes was developed. Driving behaviour was analyzed in different timeframes prior obtained from actual driving behaviour in an urban environment collected from OBD-II adapter and GPS data logger of an instrumented vehicle. By measuring the in-vehicle accelerations, it is possible to categorize the driving behaviour into four main classes based on real-time experiments: safe drivers, normal, aggressive, and dangerous drivers. When the vehicle is in a risk situation, the system based on NRF24L01+PA/LNA, GPS, and OBD-II will pass a signal to the driver using a dedicated LCD and LED light signal. The driver can instantly decide to make the vehicle in a safe mood, effectively avoid the happening of vehicle accidents. The proposed solution provides two main functions: (1) the detection of the dangerous vehicles involved in the road, and (2) the display of a message informing the driver if it is safe or unsafe to pass. System performance was evaluated to ensure that it achieved the primary objective of improving road safety in the extreme behaviour of the driver in question either the safest (or the least aggressive) and the most unsafe (or the most aggressive). The proposed methodology has retained some advantages for other literature studies because of the simultaneous use of speed, acceleration, and vehicle location. The V2V based on driving behaviour experiments shows the effectiveness of the selected approach predicts behaviour with an accuracy of over 87% in sixty-four real-time scenarios presented its capability to detect behaviour and provide a warning to nearby drivers. The system failed detection only in few times when the receiving vehicle missed data due to high speed during the test as well as the distances between the moving vehicles, the data was not received correctly since the power transmitted, the frequency range of the signals, the antenna relative positions, and the number of in-range vehicles are of interest for the V2V test scenarios. The latter result supports the conclusion that warnings that efficiently and quickly transmit their information may be better when driver are under stress or time pressure

Performance and Reliability Evaluation for DSRC Vehicular Safety Communication

<p>Inter-Vehicle Communication (IVC) is a vital part of Intelligent Transportation System (ITS), which has been extensively researched in recent years. Dedicated Short Range Communication (DSRC) is being seriously considered by automotive industry and government agencies as a promising wireless technology for enhancing transportation safety and efficiency of road utilization. In the DSRC based vehicular ad hoc networks (VANETs), the transportation safety is one of the most crucial features that needs to be addressed. Safety applications usually demand direct vehicle-to-vehicle ad hoc communication due to a highly dynamic network topology and strict delay requirements. Such direct safety communication will involve a broadcast service because safety information can be beneficial to all vehicles around a sender. Broadcasting safety messages is one of the fundamental services in DSRC. In order to provide satisfactory quality of services (QoS) for various safety applications, safety messages need to be delivered both timely and reliably. To support the stringent delay and reliability requirements of broadcasting safety messages, researchers have been seeking to test proposed DSRC protocols and suggesting improvements. A major hurdle in the development of VANET for safety-critical services is the lack of methods that enable one to determine the effectiveness of VANET design mechanism for predictable QoS and allow one to evaluate the tradeoff between network parameters. Computer simulations are extensively used for this purpose. A few analytic models and experiments have been developed to study the performance and reliability of IEEE 802.11p for safety-related applications. In this thesis, we propose to develop detailed analytic models to capture various safety message dissemination features such as channel contention, backoff behavior, concurrent transmissions, hidden terminal problems, channel fading with path loss, multi-channel operations, multi-hop dissemination in 1-Dimentional or 2-Dimentional traffic scenarios. MAC-level and application-level performance metrics are derived to evaluate the performance and reliability of message broadcasting, which provide insights on network parameter settings. Extensive simulations in either Matlab or NS2 are conducted to validate the accuracy of our proposed models.</p>Dissertatio

On the Secure and Resilient Design of Connected Vehicles: Methods and Guidelines

Vehicles have come a long way from being purely mechanical systems to systems that consist of an internal network of more than 100 microcontrollers and systems that communicate with external entities, such as other vehicles, road infrastructure, the manufacturer’s cloud and external applications. This combination of resource constraints, safety-criticality, large attack surface and the fact that millions of people own and use them each day, makes securing vehicles particularly challenging as security practices and methods need to be tailored to meet these requirements.This thesis investigates how security demands should be structured to ease discussions and collaboration between the involved parties and how requirements engineering can be accelerated by introducing generic security requirements. Practitioners are also assisted in choosing appropriate techniques for securing vehicles by identifying and categorising security and resilience techniques suitable for automotive systems. Furthermore, three specific mechanisms for securing automotive systems and providing resilience are designed and evaluated. The first part focuses on cyber security requirements and the identification of suitable techniques based on three different approaches, namely (i) providing a mapping to security levels based on a review of existing security standards and recommendations; (ii) proposing a taxonomy for resilience techniques based on a literature review; and (iii) combining security and resilience techniques to protect automotive assets that have been subject to attacks. The second part presents the design and evaluation of three techniques. First, an extension for an existing freshness mechanism to protect the in-vehicle communication against replay attacks is presented and evaluated. Second, a trust model for Vehicle-to-Vehicle communication is developed with respect to cyber resilience to allow a vehicle to include trust in neighbouring vehicles in its decision-making processes. Third, a framework is presented that enables vehicle manufacturers to protect their fleet by detecting anomalies and security attacks using vehicle trust and the available data in the cloud