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IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES 

Optimal Capacity-Delay Tradeoff in MANETs with Correlation of Node Mobility

Abstract—

In this paper, we analyze the capacity and delay in mobile ad hoc networks (MANETs) considering the correlation of node mobility (correlated mobility). Previous works on correlated mobility investigated the maximum capacity with the corresponding delay in several sub-case, the problem of optimal capacity under various delay constraints (the optimal capacity delay trade off) still remains open. To this end, we deeply explore the characteristics of correlated mobility, and figure out the fundamental relationships between the network performance and
scheduling parameters. Based on that we establish the overall upper bound of capacity-delay tradeoff in all the sub-case of correlated mobility. Then we try to obtain the achievable lower bound by identifying the optimal scheduling parameters on certain constrains. Results demonstrates the whole picture of how the correlation of node mobility impacts the capacity, delay and the corresponding tradeoff between them.

CONTACT:
GANESAN.P
+91 9865862045
+91  8903410319
1519112697
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES Optimal Capacity-Delay Tradeoff in MANETs with Correlation of Node Mobility Abstract— In this paper, we analyze the capacity and delay in mobile ad hoc networks (MANETs) considering the correlation of node mobility (correlated mobility). Previous works on correlated mobility investigated the maximum capacity with the corresponding delay in several sub-case, the problem of optimal capacity under various delay constraints (the optimal capacity delay trade off) still remains open. To this end, we deeply explore the characteristics of correlated mobility, and figure out the fundamental relationships between the network performance and scheduling parameters. Based on that we establish the overall upper bound of capacity-delay tradeoff in all the sub-case of correlated mobility. Then we try to obtain the achievable lower bound by identifying the optimal scheduling parameters on certain constrains. Results demonstrates the whole picture of how the correlation of node mobility impacts the capacity, delay and the corresponding tradeoff between them. CONTACT: GANESAN.P +91 9865862045 +91 8903410319
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES 

On the Feasibility of Full-Duplex Relaying in Multiple-Antenna Cellular Networks

Abstract—

In this paper, we perform a system-level feasibility analysis of full-duplex (FD) relay-aided cellular networks that are equipped with multiple antennas at the base stations (BSs) and relay nodes (RNs). The aim is to understand whether FD relaying is capable of enhancing the rate of cellular networks. With the aid of tools from stochastic geometry, we develop a tractable approach for computing the percentile rate, which
allows us to gain insights on the impact of FD relaying for both cell-edge and cell-median mobile terminals (MTs) subject to network interference. Contrary to previous works that do not take into account the network interference, the framework reveals that even in the absence of self interference at the FD RNs a network with half-duplex (HD) RNs can outperform its FD counterpart for a moderate number of antennas at the BSs and RNs. On the other hand, the FD-based network can substantially outperform both the HD-based one and the one without RNs for a sufficiently large number of antennas at the BSs and RNs and substantially small self-interference power effect at the RNs. Finally, the aforementioned analytical insights are validated by
means of Monte Carlo simulations. 


CONTACT:
GANESAN.P
+91 9865862045
+91  8903410319
1519112607
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES On the Feasibility of Full-Duplex Relaying in Multiple-Antenna Cellular Networks Abstract— In this paper, we perform a system-level feasibility analysis of full-duplex (FD) relay-aided cellular networks that are equipped with multiple antennas at the base stations (BSs) and relay nodes (RNs). The aim is to understand whether FD relaying is capable of enhancing the rate of cellular networks. With the aid of tools from stochastic geometry, we develop a tractable approach for computing the percentile rate, which allows us to gain insights on the impact of FD relaying for both cell-edge and cell-median mobile terminals (MTs) subject to network interference. Contrary to previous works that do not take into account the network interference, the framework reveals that even in the absence of self interference at the FD RNs a network with half-duplex (HD) RNs can outperform its FD counterpart for a moderate number of antennas at the BSs and RNs. On the other hand, the FD-based network can substantially outperform both the HD-based one and the one without RNs for a sufficiently large number of antennas at the BSs and RNs and substantially small self-interference power effect at the RNs. Finally, the aforementioned analytical insights are validated by means of Monte Carlo simulations. CONTACT: GANESAN.P +91 9865862045 +91 8903410319
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES 

On Optimal Infrastructure Sharing Strategies in Mobile Radio Networks

Abstract

The rapid evolution of mobile radio network technologies poses severe technical and economical challenges to Mobile Network Operators (MNOs); on the economical side, the continuous roll-out of technology updates is highly expensive, which may lead to the extreme where offering advanced mobile services becomes no longer affordable for MNOs which thus are not incentivized to innovate. Mobile infrastructure sharing among MNOs becomes then an important building block to lower the required per-MNO investment cost involved in the technology roll-out and management phases. We focus on a Radio Access Network (RAN) sharing situation where multiple MNOs with a consolidated network infrastructure coexist in a given set of geographical areas; the MNOs have then to decide if it is profitable to upgrade their RAN technology by deploying additional small-cell base
stations and whether to share the investment (and the deployed infrastructure) of the new small-cells with other operators. We address such strategic problem by giving a mathematical framework for the RAN infrastructure sharing problem which returns the “best” infrastructure sharing strategies for operators (coalitions and network configuration) when varying techno-economic parameters such as the achievable throughput in different sharing configurations and the pricing models for the service offered to the users. The proposed formulation is then leveraged to analyze the impact of the aforementioned parameters/input in a realistic mobile network environment based on LTE technology.


CONTACT:
GANESAN.P
+91 9865862045
+91  8903410319
1519112433
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES On Optimal Infrastructure Sharing Strategies in Mobile Radio Networks Abstract The rapid evolution of mobile radio network technologies poses severe technical and economical challenges to Mobile Network Operators (MNOs); on the economical side, the continuous roll-out of technology updates is highly expensive, which may lead to the extreme where offering advanced mobile services becomes no longer affordable for MNOs which thus are not incentivized to innovate. Mobile infrastructure sharing among MNOs becomes then an important building block to lower the required per-MNO investment cost involved in the technology roll-out and management phases. We focus on a Radio Access Network (RAN) sharing situation where multiple MNOs with a consolidated network infrastructure coexist in a given set of geographical areas; the MNOs have then to decide if it is profitable to upgrade their RAN technology by deploying additional small-cell base stations and whether to share the investment (and the deployed infrastructure) of the new small-cells with other operators. We address such strategic problem by giving a mathematical framework for the RAN infrastructure sharing problem which returns the “best” infrastructure sharing strategies for operators (coalitions and network configuration) when varying techno-economic parameters such as the achievable throughput in different sharing configurations and the pricing models for the service offered to the users. The proposed formulation is then leveraged to analyze the impact of the aforementioned parameters/input in a realistic mobile network environment based on LTE technology. CONTACT: GANESAN.P +91 9865862045 +91 8903410319
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES 

Abstract—

Batteries of modern mobile devices remain severely limited in capacity, which makes energy consumption a key concern for mobile applications, particularly for the computation intensive video applications. Mobile devices can save energy by offloading computation tasks to the cloud; yet the energy gain must exceed the additional communication cost for cloud migration to be beneficial. The situation is further complicated with real time video applications that have stringent delay and bandwidth constraints. In this paper, we closely examine the performance and energy efficiency of representative mobile cloud applications under dynamic wireless network channels and state of-the-art mobile platforms. We identify the unique challenges and opportunities for offloading real time video applications, and develop a generic model for energy-efficient computation offloading accordingly in this context. We propose a scheduling algorithm that makes adaptive offloading decisions in fine granularity in dynamic wireless network conditions, and verify its effectiveness through trace-driven simulations. We further present case studies with advanced mobile platforms and practical applications to demonstrate the superiority of our solution and the substantial gain of our approach over baseline approaches.


CONTACT:

GANESAN.P
+91 9865862045
+91 8903410319
1519111999
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES Abstract— Batteries of modern mobile devices remain severely limited in capacity, which makes energy consumption a key concern for mobile applications, particularly for the computation intensive video applications. Mobile devices can save energy by offloading computation tasks to the cloud; yet the energy gain must exceed the additional communication cost for cloud migration to be beneficial. The situation is further complicated with real time video applications that have stringent delay and bandwidth constraints. In this paper, we closely examine the performance and energy efficiency of representative mobile cloud applications under dynamic wireless network channels and state of-the-art mobile platforms. We identify the unique challenges and opportunities for offloading real time video applications, and develop a generic model for energy-efficient computation offloading accordingly in this context. We propose a scheduling algorithm that makes adaptive offloading decisions in fine granularity in dynamic wireless network conditions, and verify its effectiveness through trace-driven simulations. We further present case studies with advanced mobile platforms and practical applications to demonstrate the superiority of our solution and the substantial gain of our approach over baseline approaches. CONTACT: GANESAN.P +91 9865862045 +91 8903410319
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES 


Multi-Objective Optimization in Dynamic Content Adaptation of Slide Documents

Abstract—

In mobile Web conferencing, slide decks should be optimized before delivery to meet the constraints and environments of target mobile devices. To deliver optimally adapted slides, a trade-off between the visual aspect and delivery time must be reached. Static adaptation methods are CPU-intensive, and require large storage space. The dynamic approach is attractive as the optimal version is created on the fly when the actual slide is to be shared. Existing dynamic solutions are optimized for the resolution of the target mobile device and use good visual quality settings. However, they do not control the resulting data
size, which creates serious usability issues, such as increasing the delivery time. Prediction-based methods require much less memory and processing resources than static approaches while yielding an excellent user experience. In this paper, we propose a multi-objective dynamic content adaptation framework, in which we maximize the visual quality and minimize the delivery time simultaneously. We compare our solution with an ideal optimal point, called utopia, and with all the optimal solutions (Pareto front) provided by a static exhaustive system. The obtained results show that our framework yields solutions very close to the utopia and, for the majority of the documents tested, the obtained solutions are on the Pareto front.


CONTACT:

GANESAN.P
+91  9865862045
+91  8903410319
1518591101
IEEE 2017 - 18 MOBILE COMPUTING PROJECT TITLES Multi-Objective Optimization in Dynamic Content Adaptation of Slide Documents Abstract— In mobile Web conferencing, slide decks should be optimized before delivery to meet the constraints and environments of target mobile devices. To deliver optimally adapted slides, a trade-off between the visual aspect and delivery time must be reached. Static adaptation methods are CPU-intensive, and require large storage space. The dynamic approach is attractive as the optimal version is created on the fly when the actual slide is to be shared. Existing dynamic solutions are optimized for the resolution of the target mobile device and use good visual quality settings. However, they do not control the resulting data size, which creates serious usability issues, such as increasing the delivery time. Prediction-based methods require much less memory and processing resources than static approaches while yielding an excellent user experience. In this paper, we propose a multi-objective dynamic content adaptation framework, in which we maximize the visual quality and minimize the delivery time simultaneously. We compare our solution with an ideal optimal point, called utopia, and with all the optimal solutions (Pareto front) provided by a static exhaustive system. The obtained results show that our framework yields solutions very close to the utopia and, for the majority of the documents tested, the obtained solutions are on the Pareto front. CONTACT: GANESAN.P +91 9865862045 +91 8903410319

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