Karim Habak

COSMOS: computation offloading as a service for mobile devices

There is great potential for boosting the performance of mobile devices by offloading computation-intensive parts of mobile applications to the cloud. The full realization of this potential is hindered by a mismatch between how individual mobile devices demand computing resources and how cloud providers offer them: offloading requests from a mobile device usually require quick response, may be infrequent, and are subject to variable network connectivity, whereas cloud resources incur relatively long setup times, are leased for long time quanta, and are indifferent to network connectivity. In this paper, we present the design and implementation of the COSMOS system, which bridges this gap by providing computation offloading as a service to mobile devices. COSMOS efficiently manages cloud resources for offloading requests to both improve offloading performance seen by mobile devices and reduce the monetary cost per request to the provider. COSMOS also effectively allocates and schedules offloading requests to resolve the contention for cloud resources. Moreover, COSMOS makes offloading decisions in a risk-controlled manner to overcome the uncertainties caused by variable network connectivity and program execution. We have implemented COSMOS for Android and explored its design space through computation offloading experiments to Amazon EC2 across different applications and in various settings. We find that COSMOS, configured with the right design choices, has significant potential in reducing the cost of providing cloud resources to mobile devices while at the same time enabling mobile computation speedup.

A location-aided routing protocol for cognitive radio networks

Multi-hop cognitive radio networks (CRNs) are gaining interest recently in many practical applications. With location information becoming more available, designing location-aware routing protocols that fit the nature of CRNs becomes a necessity. We present LAUNCH as a location-aided routing protocol for CRNs that has a set of desirable properties: efficient use of the common control channel, has a minimal route setup delay, prefers stable routes, handles primary users heterogeneity, and handles secondary users mobility. LAUNCH is based on four main concepts: (1) a novel location-aware CRN routing metric that takes into account the PUs activity; (2) distributed calculations at the neighbors; (3) a channel locking mechanism to achieve the route stability and minimize channel switching time; (4) an efficient route maintenance strategy. Evaluation of LAUNCH on the NS2 simulator shows that its performance significantly outperforms the current state-of-the-art CRNs routing protocols in terms of end-to-end delay and packet loss rate. In addition, LAUNCH incurs a low control overhead with a fast route establishment delay.

Bandwidth aggregation techniques in heterogeneous multi-homed devices

The widespread deployment of various networking technologies, coupled with the exponential increase in end-user data demand, have led to the proliferation of multi-homed, or multi-interface enabled devices. These trends drove researchers to investigate a wide spectrum of solutions, at different layers of the protocol stack, that utilize available interfaces in such devices by aggregating their bandwidth. In this survey paper, we provide an overview and examine the evolution of bandwidth aggregation solutions over time. We begin by describing the bandwidth aggregation problem. We then investigate the common features of proposed bandwidth aggregation systems and break them down into two major categories: layer-dependent and layer-independent features. Afterwards, we discuss the evolution trends in the literature and share some open challenges requiring further research. We end the survey with a brief presentation of related work in tangential research areas.

Towards Mobile Opportunistic Computing

With the advent of wearable computing and the resulting growth in mobile application market, we investigate mobile opportunistic cloud computing where mobile devices leverage nearby computational resources in order to save execution time and consumed energy. Our goal is to enable generic computation offloading to heterogeneous devices that include Cloud, mobile devices, and cloudlets. We propose a generic and flexible architecture that maximizes the computation gain with respect to various objective functions such as, minimizing the response time, reducing the overall energy consumption, and increasing the network lifetime. This novel architecture is designed to automate computation offloading to numerous compute resources over disrupted network connections.

Dead zone penetration protocol for cognitive radio networks

Current routing protocols for cognitive radio networks are severely affected by the frequent activity of primary users. Nodes that are in the interference range of an appearing primary user are not allowed to transmit, and therefore existing routes which utilize such nodes are obliged to undergo a route maintenance phase. This naturally provides other routes to the destination that may incur extra delay or increase packet queuing overhead. In this work, a novel route maintenance protocol is proposed that allows existing routes to endure the event of primary user presence by forming cooperative links between neighboring nodes and nulling out transmission at the primary receiver using cooperative beamforming. Our proposed protocol can be used in conjunction with any of the existing routing protocols, thus achieving modularity. Extensive simulations are done which prove that our proposed protocol outperforms existing route maintenance techniques in terms of end-to-end delay and loss ratio, with minimal incurred overhead.

An optimal deployable bandwidth aggregation system

The explosive increase in data demand coupled with the rapid deployment of various wireless access technologies have led to the increase of number of multi-homed or multi-interface enabled devices. Fully exploiting these interfaces has motivated researchers to propose numerous solutions that aggregate their available bandwidths to increase overall throughput and satisfy the end-users growing data demand. These solutions, however, do not utilize their interfaces to the maximum without network support, and more importantly, have faced a steep deployment barrier. In this paper, we propose an optimal deployable bandwidth aggregation system (DBAS) for multi-interface enabled devices. We present the DBAS architecture that does not introduce any intermediate hardware, modify current operating systems, modify socket implementations, nor require changes to current applications or legacy servers. The DBAS architecture is designed to automatically estimate the characteristics of applications and dynamically schedule various connections and/or packets to different interfaces. We also formulate our optimal scheduler as a mixed integer programming problem yielding an efficient solution. We evaluate DBAS via implementation on the Windows OS and further verify our results with simulations on NS2. Our evaluation shows that, with current Internet characteristics, DBAS reaches the throughput upper bound with no modifications to legacy servers. It also highlights the significant enhancements in the response time introduced by DBAS, which directly enhances the user experience.

OPERETTA: An optimal energy efficient bandwidth aggregation system

The widespread deployment of varying networking technologies, coupled with the exponential increase in end-user data demand, have led to the proliferation of multi-homed or multi-interface enabled devices. To date, these interfaces are mainly utilized one at a time based on network availability, cost, and user-choice. While researchers have focused on simultaneously leveraging these interfaces by aggregating their bandwidths, these solutions however, have faced a steep deployment barrier. In this paper, we propose a novel optimal, energy-efficient, and deployable bandwidth aggregation system (OPERETTA) for multiple interface enabled devices. OPERETTA satisfies three goals: achieving a user defined throughput level with optimal energy consumption over multiple interfaces, deployability without changes to current legacy servers, and leveraging incremental deployment to achieve increased performance gains. We present the OPERETTA architecture and formulate the optimal scheduling problem as a mixed integer programming problem yielding an efficient solution. We evaluate OPERETTA via implementation on the the Windows OS, and further verify our results with simulations on NS2. Our evaluation shows the tradeoffs between the energy and throughput goals. Furthermore, with no modifications to current legacy servers, OPERETTA achieves throughput gains up to 150% compared to current operating systems with the same energy consumption. In addition, with as few as 25% of the servers becoming OPERETTA enabled, OPERETTA performance reaches the throughput upper bound, highlighting its incremental deployment and performance gains.

DBAS: A Deployable Bandwidth Aggregation System

The explosive increase in data demand coupled with the rapid deployment of various wireless access technologies have led to the increase of number of multi-homed or multi-interface enabled devices. Fully exploiting these interfaces has motivated researchers to propose numerous solutions that aggregate their available bandwidths to increase overall throughput and satisfy the end-users growing data demand. These solutions, however, have faced a steep deployment barrier that we attempt to overcome in this paper. We propose a Deployable Bandwidth Aggregation System (DBAS) for multi-interface enabled devices. Our system does not introduce any intermediate hardware, modify current operating systems, modify socket implementations, nor require changes to current applications or legacy servers. The DBAS architecture is designed to automatically estimate the characteristics of applications and dynamically schedule various connections or packets to different interfaces. Since our main focus is deployability, we fully implement DBAS on the Windows operating system and evaluate various modes of operation. Our implementation and simulation results show that DBAS achieves up to more than double the throughput gains compared to current operating systems, while operating as an out-of-the-box standard Windows executable, highlighting its deployability.

G-DBAS: A green and deployable bandwidth aggregation system

The widespread deployment of varying networking technologies, coupled with the exponential increase in end-user data demand, have all led to the proliferation of multi-homed or multi-interface enabled devices. To date, these interfaces are mainly utilized one at a time based on network availability, cost, and user-choice. Researchers have recently focused on leveraging these interfaces simultaneously by proposing solutions to aggregate their bandwidths in order to ultimately increase throughput and satisfy the end-users growing demand on data. These solutions, however, have faced a steep deployment barrier due to various system design choices and heavy demand on energy. In this paper, we propose a novel Green and Deployable Bandwidth Aggregation System (G-DBAS) for multiple interface enabled devices. G-DBAS addresses a set of challenges including automatically estimating the characteristics of applications and scheduling various connections to different interfaces along with meeting different energy consumption goals set by users. We fully implement G-DBAS on the Windows OS and evaluate various scheduling strategies that we propose. Our implementation and simulation results show that G-DBAS can achieve the user energy-throughput goals while operating as an out-of-the-box standard Windows executable, highlighting its deployability and ease of use.

What Goes Around Comes Around: Mobile Bandwidth Sharing and Aggregation

The exponential increase in mobile data demand, coupled with growing user expectation to be connected in all places at all times, have introduced novel challenges for researchers to address. Fortunately, the wide spread deployment of various network technologies and the increased adoption of multi-interface-enabled devices allow researchers to develop solutions for those challenges. Such solutions exploit available interfaces on these devices in both local and collaborative forms. These solutions, however, have faced a formidable deployment barrier. Therefore, in this paper, we present OSCAR, a multi-objective, incentive-based, collaborative, and deployable bandwidth aggregation system, designed to exploit multiple network interfaces on modern mobile devices. Oscars architecture does not introduce any intermediate hardware nor require changes to current applications or legacy servers. This architecture estimates the interfaces characteristics and application requirements, schedules various connections and/or packets to different interfaces, and provides users with incentives for collaboration and bandwidth sharing. We formulate the OSCAR scheduler as a multi-objective scheduler that maximizes system throughput while achieving user-defined efficiency goals for both cost and energy consumption. We implement a small scale prototype of our OSCAR system, which we use to evaluate its performance. Our evaluation shows that we provide up to 150% enhancement in the throughput compared to current operating systems with only minor updates to the client devices.