Samya Bhattacharya

An energy efficient double cluster head routing scheme for motorway vehicular networks

We propose a novel double cluster-head routing scheme for motorway vehicular networks which is generically modelled (can be applied o single or multiple cluster-head routing schemes) to save a significant amount of energy through adaptive sleep cycles while maintaining he required quality of service (QoS). Real vehicular and data traffic measurements are utilised o evaluate the performance of he double cluster-head (DCH) scheme and compare with he existing (a single cluster-head (SCH)) scheme. The results, also verified with he simulations, reveal that the DCH scheme is able to achieve 2× lower packet blocking probability compared o he SCH scheme. Furthermore, on an average energy saving of 94% with service-tolerant delay during the whole day is achieved. In addition, we found ha with a lower market penetration ratio (MPR), which represents he near future vehicular communication rend, more than 4× energy is saved during peak hours in a motorway vehicular environment.

A Vacation-Based Performance Analysis of an Energy-Efficient Motorway Vehicular Communication System

Due to the unprecedented growth in bandwidth requirement, the increasing number of access points (APs) deployed within a macrocell for services such as video conferencing, video gaming, and data off-loading leads to significantly higher energy consumption. This advancement in mobile networks has forced researchers to explore various methods of energy saving, although with little emphasis on motorway vehicular networks where mobility is also an important aspect. Energy saving in these networks is extremely challenging due to the dynamic nature of the environment in which they operate. To analyze such a network, we first develop a performance model for a medium access control (MAC) protocol, namely, the modified version of packet reservation multiple access (M-PRMA) with wireless channel impairments in a motorway vehicular environment. The M-PRMA protocol provides communication links (time slots) between an AP and the vehicles in range. The time slots of the M-PRMA protocol are modeled as servers where each outage of the channel is represented as a server on queue-length-independent vacation. Then, each AP, in a hierarchical micro-macro topology, is modeled as a single-server queue where the AP takes queue-length-dependent vacations (switches to sleep mode) to save energy during its inactivity period, although at the expense of degraded quality of service (QoS). To address this, a number of sleep strategies for the AP are studied. Finally, both of these proposed models (M-PRMA with channel impairments and AP with sleep cycles) are analyzed and verified through simulations. The performance results reveal that the introduction of sleep strategies at an AP can save up to 80% transmission energy during off-peak hours and 66% on average during the day in a motorway vehicular environment while supporting end-to-end QoS for video and audio conferencing applications.

Greening vehicular networks with standalone wind powered RSUs: A performance case study

The need for reducing the carbon footprint and reducing the operation expenditure (OPEX) in communication networks poses several challenges in the study, design and deployment of energy efficient networks in different environments. Recently there has been a considerable effort to green vehicular networks which is very challenging due to the very dynamic environment in which these networks operate. In this paper, we investigate the performance of the roadside units (RSUs) in a vehicular motorway network, and propose that these units are wind-powered and act as standalone entities. Real vehicular traffic profiles, reported data traffic measurements and reported wind measurements have been utilised to perform this study. We analyse the performance in several test cases and suggest an operational scenario. Both analytical and simulation results reveal that with the introduction of sleep cycles and a very small battery capacity (124 mAh), these RSUs are able to support quality of service (QoS) for video-related applications at each hour of the day in a motorway vehicular environment while increasing the energy efficiency by up to 32%.

Load Adaptive Caching Points for a Content Distribution Network

The unprecedented growth in content demand on smartphones has significantly increased the energy consumption of current cellular and backbone networks. Apart from achieving stringent carbon footprint targets, provisioning high data rates to city vehicular users while maintaining quality of service (QoS) remains a serious challenge. In previous work, to support content delivery at high data rates, the number and locations of caching points (CPs) within a content distribution network (CDN) were optimized while reducing the operational energy consumption compared to typical cellular networks. Further reduction in energy consumption may be possible through sleep cycles, which reduces transmission energy consumption. However, sleep cycles degrade the quality of service. Therefore, in this paper, we propose a novel load adaptation technique for a CP which not only enhances content download rate but also reduces transmission energy consumption through random sleep cycles. Unlike a non-load adaptive (deterministic) CP, the performance results reveal that the load adaptive CP achieves considerably lower average piece delay (approximately 60% on average during the day), leveraging the introduction of random sleep cycles to save transmission energy. The proposed CP saves up to 84% transmission energy during off-peak hours and 33% during the whole day while fulfilling content demand in a city vehicular environment.

A 3-D Markov Chain Model for a Multi-Dimensional Indoor Environment

In this paper, a pico-cellular airport traffic model is proposed which supports Engset distributed fresh call arrival process and General distributed handoff process with Dynamic Channel Allocation (DCA). The proposed model enables load balancing using DCA and uses a three-dimensional Markov chain to compute traffic congestion and call congestion for any kind of traffic streams, including Pure Chance Type-I (PCT-I) or Pure Chance Type-II (PCT-II). The application of the proposed model is illustrated in assessing indoor mobility to evaluate QoS parameters. The proposed airport traffic model is fairly general in the sense that it is not restricted by number of users, user mobility or range of offered load, and can be reduced to predict congestion for Poisson distributed fresh call arrival processes and General distributed handoff processes.

Reliability and quality of service of an off-grid wind powered roadside unit in a motorway vehicular environment

Wind-powered base stations and roadside units have been considered as a cost effective greening solution in windy countries which also have limited solar irradiation. The practicality of such a system increases significantly in sparse areas such as countryside and motorways. The deployment of standalone off-grid wind powered roadside units could alleviate the common issues related to grid connected renewable energy farms. Hence, there is need to study the feasibility of an off-grid wind powered roadside unit for seamless connectivity. Unlike the conventional usage of reliability analysis of fault-tolerant systems, in this paper, reliability is redefined in the context of availability of intermittent wind for powering a roadside unit (RSU) in a UK motorway vehicular environment. Transient analysis of energy consumption (energy demand) of the RSU and harnessed wind energy are carried out along with real measurements for developing respective generic energy models. Further, a generalised methodology is developed to determine the minimum battery size for achieving a certain reliability standard and quality of service. Several reliability indices such as loss of load probability (LOLP), loss of load expectation (LOLE), energy index of reliability (EIR), mean time between failures (MTBF), mean time to recovery (MTTR), forced outage rate (FOR), etc. are obtained for the RSU. The performance results reveal that with a standard micro-turbine and a reasonably small battery, an RSU achieves a good reliability of 99.9% with significant improvement in the quality of service.

Sleep-enabled roadside units for motorway vehicular networks

In this paper, we introduce a number of generic sleep mechanisms for energy saving at the vehicular roadside units (RSUs). Since random sleep cycles (sleep cycles type-I) were already introduced before, we term the introduced mechanisms sleep cycles (type-II, III, IV, V, VI). Each sleep cycles type arranges the service and sleep sequences distinctively to yield various levels of energy savings and average packet delay. A generic analytic model for the roadside unit (RSU) with such sleep cycles is proposed using G/G/1/K G-vacation queuing, where real vehicular traffic profiles and packet size measurements are utilised. The performance evaluation reveals that with one of the proposed sleep cycles (type-IV), the RSU achieves 68% energy savings and 7.3 ms average packet delay over the day, resulting in respective improvements of 10% and 28% compared to the existing random sleep cycles. These improvements have been achieved under a very conservative operating delay bound for audio conferencing applications. However, modern compression and codecs, due to their leniency on Quality of Service (QoS), would potentially enable higher energy savings through the proposed sleep cycles.

Wind Energy Dependent Rate Adaptation for Roadside Units

In this paper, we propose a rate adaptive technique for wind powered standalone (off-grid) roadside units (RSUs) in a motorway environment. In a non-rate adaptive system, the transient nature of renewable wind energy causes the RSUs to either transmit at full data rate or not transmit at all based on the availability of sufficient energy. In rate adaptation, the data rate of an RSU adapts according to the available energy. Further, the RSU saves transmission energy by operating at a lower data rate, even when enough energy is available. The saved energy, in turn, is used to maintain the data rate during energy deficiency, thereby minimizing outage and improving the quality of service (QoS). The performance analysis shows that the wind energy dependent rate adaptive RSU delivers a more energy efficient service with acceptable quality compared to a non-rate adaptive deployment in a renewable energy solely powered RSU. The proposed rate adaptive algorithm can be as well deployed to wind-powered communication base stations (BSs) and sensor networks.

On Indoor Mobility Performance Limits for an Engset Radio-over-Fiber Model Using Prioritized General Handoff Process

The application of Radio-over-Fiber (RoF) technology in cellular systems has attracted considerable attention in recent time. Consequently, the indoor personal communication systems (PCS) using the RoF architecture needs reinvestigation in performance domain. In this paper, we investigate such a system, which uses tiny cells (pico-cells) with limited number of users. We develop a corresponding traffic model for state dependent fresh call requests (Engset distribution) from limited user population. The model, in addition, considers frequent handoffs of users, which is not necessarily a memoryless random process. The model has a provision of channel reservation for handoff calls thereby prioritize the handoff process. The proposed model is computationally efficient and simple to implement. Further, it is effective to determine the optimum level of reservation in system design.

Energy efficient Nano Servers provisioning for Information Piece Delivery in a vehicular environment

In this paper, we propose energy efficient Information Piece Delivery (IPD) through Nano Servers (NSs) in a vehicular network. Information pieces may contain any data that needs to be communicated to a vehicle. The available power (renewable or non-renewable) for a NS is variable. As a result, the service rate of a NS varies linearly with the available energy within a given range. Our proposed system therefore exhibits energy aware rate adaptation (RA), which uses variable transmission energy. We have also developed another transmission energy saving method for comparison, where sleep cycles (SC) are employed. Both methods are compared against an acceptable download time. To reduce the operational energy, we first optimise the locations of the NSs by developing a mixed integer linear programming (MILP) model, which takes into account the hourly variation of the traffic. The model is validated through a Genetic Algorithm (GA1). Furthermore, to reduce the gross delay over the entire vehicular network, the available renewable energy (wind farm) is optimally allocated to each NS according to piece demand. This, in turn, also reduces the network carbon footprint. A Genetic Algorithm (GA2) is also developed to validate the MILP results associated with this system. Through transmission energy savings, RA and SC further reduce the NSs energy consumption by 19% and 18% respectively, however at the expense of higher download time. MILP model 4 (with RA) and model 5 (with SC) reduced the delay by 81% and 83% respectively, while minimising the carbon footprint by 96% and 98% respectively, compared to the initial MILP model.