Jagruti Sahoo

Congestion-Controlled-Coordinator-Based MAC for Safety-Critical Message Transmission in VANETs

Vehicular ad hoc networks (VANETs) provide the communication framework for the dissemination of safety-critical messages such as beacons and emergency messages. The communication channel witnesses significant network load generated by frequently exchanged beacons. Under high-density situations, it leads to a serious scalability problem in VANETs. Moreover, contention-based medium access control (MAC) protocols suffer from a great number of packet collisions, and as a result, the reliability and latency of safety messages are severely affected. Because of the periodic nature of beacons, time-division multiple access (TDMA) can be a good choice over contention-based MAC. In this paper, we propose congestion-controlled-coordinator-based MAC (CCC-MAC), which is a time-slot-based medium access protocol that addresses beacons and emergency messages. Basically, the network is virtually partitioned into a number of segments. Within a segment, medium access is accomplished by using a time-slot-scheduling mechanism supervised by a local coordinator vehicle. A significant number of vehicles can be supported under the proposed configuration. In fact, the proposed scheduling mitigates channel congestion by reducing the transmission time of beacons through the use of multiple data rates. Bandwidth utilization is also improved by reusing the unoccupied time slots. Finally, CCC-MAC ensures fast and reliable propagation of emergency messages by employing a pulse-based reservation mechanism. In the simulations, we demonstrate the ability of CCC-MAC to scale well in different vehicular density scenarios. Moreover, it outperforms existing MAC-layer protocols with respect to packet reception probability and latency of safety messages.

Agile Urban Parking Recommendation Service for Intelligent Vehicular Guiding System

Nowadays, Intelligent Transportation Systems (ITS) technologies are exploring a wide range of services such as freeway management, crash prevention & safety, driver assistance, and infotainment of drivers and/or passengers. In this paper, an agile urban parking recommendation service for vehicular intelligent guiding system is designed to facilitate city citizens with fully efficient, real-time and precise parking lot guiding suggestions for the sustainability of the future green city. The system offers drivers a friendly parking lot recommendation sequence and saves drivers time circling around by the accurate prediction of the successful parking probability in each parking lot. The proposed cost model constructs an optimal recommendation sequence considering successful parking probability and time to reach the parking lot. Through the collection and analysis of realistic records from parking lots in Taipei city, a prediction algorithm is developed to estimate the successful parking probability by using current available space counts. Extensive experiments are conducted to demonstrate the effectiveness of the prediction algorithm.

Optimal selection of aggregation locations for participatory sensing by mobile cyber-physical systems

Mobile cyber-physical systems entail large volumes of data collected by various sensors and cameras embedded in vehicles and mobile devices. Participatory sensing is a model widely encouraged by cyber-physical systems (CPS) to provide a smart knowledge base to consumers using various sensed data contributed by voluntary participants. Aggregation is a viable approach to convert the sensed data into a usable form. An efficient way to perform aggregation is to divide the network into a number of geographical regions, called aggregation regions. In this paper, we propose a novel mechanism to determine aggregation regions based on the location of Access Points (APs). Besides, we propose a strategy to determine the optimal location of aggregation that minimizes the delay of dissemination of sensed data.

Cloudifying the 3GPP IP multimedia subsystem for 4G and beyond: A survey

4G systems have been continuously evolving to cope with the emerging challenges of human-centric and M2M applications. Research has also now started on 5G systems. Scenarios have been proposed and initial requirements derived. 4G and beyond systems are expected to easily deliver a wide range of human-centric and M2M applications and services in a scalable, elastic, and cost-efficient manner. The 3GPP IMS was standardized as the service delivery platform for 3G networks. Unfortunately, it does not meet several requirements for provisioning applications and services in 4G and beyond systems. However, cloudifying it will certainly pave the way for its use as a service delivery platform for 4G and beyond. This article presents a critical overview of the architectures proposed so far for cloudifying the IMS. There are two classes of approaches; the first focuses on the whole IMS system, and the second deals with specific IMS entities. Research directions are also discussed. IMS granularity and a PaaS for the development and management of IMS functional entities are the two key directions we currently foresee.

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Content delivery networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and quality of service of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and network functions virtualization, new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm-based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs.

NFV based gateways for virtualized wireless sensor networks: A case study

Virtualization enables the sharing of a same wireless sensor network (WSN) by multiple applications. However, in heterogeneous environments, virtualized wireless sensor networks (VWSN) raise new challenges such as the need for on-the-fly, dynamic, elastic, and scalable provisioning of gateways. Network Functions Virtualization (NFV) is an emerging paradigm that can certainly aid in tackling these new challenges. It leverages standard virtualization technology to consolidate special-purpose network elements on top of commodity hardware. This article presents a case study on NFV based gateways for VWSNs. In the study, a VWSN gateway provider operates and manages an NFV based infrastructure. We use two different brands of wireless sensors. The NFV infrastructure makes possible the dynamic, elastic, and scalable deployment of gateway modules in this heterogeneous VWSN environment. The prototype built with Openstack as platform is described.

Hierarchical aggregation for delay-sensitive vehicular sensing

Vehicular sensing has gained significant attention in recent years, thanks to its enormous benefits to many entities including traffic management centers, forensic authorities and air pollution control units. To reduce redundancy and improve the content, the collected data must be aggregated. Delay-sensitive sensing applications require the aggregated data be collected with a certain delay. In this paper, we propose a hierarchical aggregation scheme for image sensing in vehicular networks. The hierarchy is dynamically updated based on observed network conditions. In particular, partition and merge operations are performed on the hierarchy to satisfy the delay requirement. The simulation results show that the proposed scheme outperforms existing scheme in terms of efficient data collection and redundancy elimination.

A novel vehicular sensing framework for smart cities

Smart cities leverage technology to analyze data to make decisions, anticipate problems and coordinate resources to operate efficiently. Data produced by sensors embedded in vehicles moving on streets enable sensing applications for smart cities that were infeasible in the past due to high deployment costs. In this paper, we propose a novel framework for collection, aggregation and retrieval of data. The framework considers vehicles and road-side units as the main entities. To collect data, the city road network is divided into a number of sensing regions. We discuss the aggregation operations for each type of event. A retrieval mechanism is also proposed to deliver content in real-time. The simulations results demonstrate that the proposed framework outperforms existing vehicular sensing approaches in terms of delay and accuracy.

A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks

This paper provides a comprehensive survey of content placement (CP) algorithms for cloud-based content delivery networks (CCDNs). CP algorithms are essential for content delivery for their major role in selecting content to be stored in the geographically distributed surrogate servers in the cloud to meet end-user demands with quality of service (QoS). Evidently, the key objectives of CP, i.e., cost and QoS, are competing. Cost is determined by the underlying cost model of the CCDN infrastructure while the delivered QoS is determined by where the content is placed in the CCDN. Therefore, we provide an overview of the content and the CCDN infrastructure. The overview of the content includes content characteristics and the influence of Online Social Networking on CP. The overview of the CCDN infrastructure includes elasticity and cost model, which affect CP. Our goal is to provide a holistic perspective of the aspects that impact CP algorithms and their efficiency. From the influential factors, we derive a set of design criteria for CP algorithms in CCDNs. We discuss the state-of-the-art CP algorithms for CCDNs and evaluate them against the well-motivated design criteria. We also delineate practical implications and uncover future research challenges.

Greedy heuristic for replica server placement in Cloud based Content Delivery Networks

Recently, Cloud based Content Delivery Network (CCDN) has emerged as efficient content delivery architecture to provide content delivery services with improved Quality of Service (QoS), scalability and resource efficiency. Replica server placement is a key design issue in CCDNs and involves deciding the placement of replica servers on geographically dispersed cloud sites that minimizes the operational cost and satisfies QoS of the end-users. Since replica server placement problem is NP-hard, it is necessary to design an efficient heuristic for CCDNs. In this paper, we propose an efficient greedy heuristic for the replica server placement problem. The heuristic consists of two main procedures: placement and refinement. The placement procedure obtains an initial placement of replica servers on cloud sites with low operational cost. The refinement procedure removes the redundant cloud sites to reduce the operational cost further. The simulation results demonstrate that the proposed greedy heuristic outperforms the existing greedy heuristics in terms of computation time and the operational cost.