Code offloading in opportunistic computing

With the advent of cloud computing, applications are no longer tied to a single device, but they can be migrated to a high-performance machine located in a distant data center. The key advantage is the enhancement of performance and consequently, the users experience. This activity is commonly referred computational offloading and it has been strenuously investigated in the past years. The natural candidate for computational offloading is the cloud, but recent results point out the hidden costs of cloud reliance in terms of latency and energy; Cuervo et. al. illustrates the limitations on cloud-based computational offloading based on WANs latency times. The dissertation confirms the results of Cuervo et. al. and illustrates more use cases where the cloud may not be the right choice. This dissertation addresses the following question: is it possible to build a novel approach for offloading the computation that overcomes the limitations of the state-of-the-art? In other words, is it possible to create a computational offloading solution that is able to use local resources when the Cloud is not usable, and remove the strong bond with the local infrastructure? To this extent, I propose a novel paradigm for computation offloading named anyrun computing, whose goal is to use any piece of higher-end hardware (locally or remotely accessible) to offloading a portion of the application. With anyrun computing I removed the boundaries that tie the solution to an infrastructure by adding locally available devices to augment the chances to succeed in offloading. To achieve the goals of the dissertation it is fundamental to have a clear view of all the steps that take part in the offloading process. To this extent, I firstly provided a categorization of such activities combined with their interactions and assessed the impact on the system. The outcome of the analysis is the mapping to the problem to a combinatorial optimization problem that is notoriously known to be NP-Hard. There are a set of well-known approaches to solving such kind of problems, but in this scenario, they cannot be used because they require a global view that can be only maintained by a centralized infrastructure. Thus, local solutions are needed. Moving further, to empirically tackle the anyrun computing paradigm, I propose the anyrun computing framework (ARC), a novel software framework whose objective is to decide whether to offload or not to any resource-rich device willing to lend assistance is advantageous compared to local execution with respect to a rich array of performance dimensions. The core of ARC is the nference nodel which receives a rich set of information about the available remote devices from the SCAMPI opportunistic computing framework developed within the European project SCAMPI, and employs the information to profile a given device, in other words, it decides whether offloading is advantageous compared to local execution, i.e. whether it can reduce the local footprint compared to local execution in the dimensions of interest (CPU and RAM usage, execution time, and energy consumption). To empirically evaluate ARC I presented a set of experimental results on the cloud, cloudlet, and opportunistic domain. In the cloud domain, I used the state of the art in cloud solutions over a set of significant benchmark problems and with three WANs access technologies (i.e. 3G, 4G, and high-speed WAN). The main outcome is that the cloud is an appealing solution for a wide variety of problems, but there is a set of circumstances where the cloud performs poorly. Moreover, I have empirically shown the limitations of cloud-based approaches, specifically, In some circumstances, problems with high transmission costs tend to perform poorly, unless they have high computational needs. The second part of the evaluation is done in opportunistic/cloudlet scenarios where I used my custom-made testbed to compare ARC and MAUI, the state of the art in computation offloading. To this extent, I have performed two distinct experiments: the first with a cloudlet environment and the second with an opportunistic environment. The key outcome is that ARC virtually matches the performances of MAUI (in terms of energy savings) in cloudlet environment, but it improves them by a 50% to 60% in the opportunistic domain

An SOA-Based Framework of Computational Offloading for Mobile Cloud Computing

Mobile Computing is a technology that allows transmission of audio, video, and other types of data via a computer or any other wireless-enabled device without having to be connected to a fixed physical link. Despite increasing usage of mobile computing, exploiting its full potential is difficult due to its inherent problems such as resource scarcity, connection instability, and limited computational power. In particular, the advent of connecting mobile devices to the internet offers the possibility of offloading computation and data intensive tasks from mobile devices to remote cloud servers for efficient execution. This proposed thesis develops an algorithm that uses an objective function to adaptively decide strategies for computational offloading according to changing context information. By following the style of Service-Oriented Architecture (SOA), the proposed framework brings cloud computing to mobile devices for mobile applications to benefit from remote execution of tasks in the cloud. This research discusses the algorithm and framework, along with the results of the experiments with a newly developed system for self-driving vehicles and points out the anticipated advantages of Adaptive Computational Offloading

Heterogeneous LTE/ Wi-Fi architecture for intelligent transportation systems

Intelligent Transportation Systems (ITS) make use of advanced technologies to enhance road safety and improve traffic efficiency. It is anticipated that ITS will play a vital future role in improving traffic efficiency, safety, comfort and emissions. In order to assist the passengers to travel safely, efficiently and conveniently, several application requirements have to be met simultaneously. In addition to the delivery of regular traffic and safety information, vehicular networks have been recently required to support infotainment services. Previous vehicular network designs and architectures do not satisfy this increasing traffic demand as they are setup for either voice or data traffic, which is not suitable for the transfer of vehicular traffic. This new requirement is one of the key drivers behind the need for new mobile wireless broadband architectures and technologies. For this purpose, this thesis proposes and investigates a heterogeneous IEEE 802.11 and LTE vehicular system that supports both infotainment and ITS traffic control data. IEEE 802.11g is used for V2V communications and as an on-board access network while, LTE is used for V2I communications. A performance simulation-based study is conducted to validate the feasibility of the proposed system in an urban vehicular environment. The system performance is evaluated in terms of data loss, data rate, delay and jitter. Several simulation scenarios are performed and evaluated. In the V2I-only scenario, the delay, jitter and data drops for both ITS and video traffic are within the acceptable limits, as defined by vehicular application requirements. Although a tendency of increase in video packet drops during handover from one eNodeB to another is observed yet, the attainable data loss rate is still below the defined benchmarks. In the integrated V2V-V2I scenario, data loss in uplink ITS traffic was initially observed so, Burst communication technique is applied to prevent packet losses in the critical uplink ITS traffic. A quantitative analysis is performed to determine the number of packets per burst, the inter-packet and inter-burst intervals. It is found that a substantial improvement is achieved using a two-packet Burst, where no packets are lost in the uplink direction. The delay, jitter and data drops for both uplink and downlink ITS traffic, and video traffic are below the benchmarks of vehicular applications. Thus, the results indicate that the proposed heterogeneous system offers acceptable performance that meets the requirements of the different vehicular applications. All simulations are conducted on OPNET Network Modeler and results are subjected to a 95% confidence analysis

Analysis, design and experimental evaluation of connectivity management in heterogeneous wireless environments

Mención Internacional en el título de doctorThe future of network communications is mobile as many more users demand for ubiquitous connectivity. Wireless has become the primary access technology or even the only one, leading to an explosion in traffic demand. This challenges network providers to manage and configure new requirements without incrementing costs in the same amount. In addition to the growth in the use of mobile devices, there is a need to operate simultaneously different access technologies. As well, the great diversity of applications and the capabilities of mobile terminals makes possible for us to live in a hyper-connected world and offers new scenarios. This heterogeneity poses great challenges that need to be addressed to offer better performance and seamless experience to the final user. We need to orchestrate solutions to increase flexibility and empower interoperability. Connectivity management is handled from different angles. In the network stack, mobility is more easily handled by IP mobility protocols, since IP is the common layer between the different access technologies and the application diversity. From the end-user perspective, the connection manager is in charge of handling connectivity issues in mobile devices, but it is an unstandardized entity so its performance is heavily implementation-dependent. In this thesis we explore connectivity management from different angles. We study mobility protocols as they are part of our proposed solutions. In most of the cases we include an experimental evaluation of performance with 3G and IEEE 802.11 as the main technologies. We consider heterogeneous scenarios, with several access technologies where mobile devices have also several network interfaces. We evaluate how connectivity is handled as well as its influence in a handover. Based on the analysis of real traces from a cellular network, we confirm the suitability of more efficient mobility management. Moreover, we propose and evaluate three different solutions for providing mobility support in three different heterogeneous scenarios. We perform an experimental evaluation of a vehicular route optimization for network mobility, reporting on the challenges and lessons learned in such a complicated networking environment. We propose an architecture for supporting mobility and enhance handover in a passive optical network deployment. In addition, we design and deploy a mechanism for mobility management based on software-defined networking.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Arturo Azcorra Saloña.- Secretario: Ramón Agüero Calvo.- Vocal: Daniel Nunes Coruj

Open Platforms for Connected Vehicles

L'abstract è presente nell'allegato / the abstract is in the attachmen