Antonio Liotta

On management technologies and the potential of Web services

From the early days of management research and standardization in the late 1980s, there has always been a quest for a management technology that would be general enough to be used for network, system, service, and distributed application management; efficient in terms of information retrieval time, computational resources required, and management traffic incurred; and easy to use in order to reduce development time and operational costs. From protocol-based approaches such as OSI management and SNMP, attention shifted to distributed object and Web-based approaches. Recently, XML-based approaches and, in particular, Web services have been emerging as a promising Internet-based technology that might also be used for management. In this article we survey first the key aspects of protocol and distributed object approaches to management. We subsequently examine Web services as a distributed object approach to management, and consider its suitability, usability, and performance in comparison to SNMP and CORBA.

QoE-aware QoS management

The streaming of multimedia contents (e.g., Mobile TV) is a bandwidth intensive service. The network operators aim is to provide an acceptable user experience at minimal network resource usage. It is important from the network operators perspective to be aware of: 1) the thresholds at which the users perception of service quality becomes unacceptable; and 2) the degree of influence of each of the Quality of Service (QoS) parameters on the user perception. However, very little is known about the formal methods to optimize the use of QoS mechanisms in relation to the users Quality of Experience (QoE). In this paper, we explain how the users QoE can be captured. A statistical modelling technique is employed which, correlates QoS parameters with estimates of QoE perceptions and identifies the degree of influence of each QoS parameters on the user perception. The network operator can apply this information to efficiently, and accurately undertake network dimensioning and service provisioning strategies. This proposed methodology is applied to demonstrate QoE management strategies, thus paving the way towards QoE-aware QoS management.

Quality of experience management in mobile content delivery systems

This study contributes towards the relatively new but growing discipline of QoE management in content delivery systems. The study focuses on the development of a QoE-based management framework for the construction of QoE models for different types of multimedia contents delivered onto three typical mobile terminals—a mobile phone, PDA and a laptop. A statistical modelling technique is employed which, correlates QoS parameters with estimates of QoE perceptions. These correlations were found to be dependent on terminals and multimedia content types. The application of the framework and prediction models in QoE management strategies are demonstrated using examples. We find that significant resource savings can be achieved with our approach by contrast to conventional QoS solutions.

Stable clustering through mobility prediction for large-scale multihop intelligent ad hoc networks

In this paper we present a framework for dynamically organizing mobile nodes (MNs) in large-scale mobile ad hoc networks (MANETs), with the eventual aim to support quality of service (QoS). Our dynamic, distributed clustering approach is based on intelligent mobility prediction that enables each MN to anticipate the availability of its neighbors. We present a scalable way to predict the mobility, and thus availability, of MNs, achieved with the introduction of geographically-oriented virtual clusters. We name the proposed model as the (p, t, d)-clustering model that facilitates the formation of stable clusters. Simulation results demonstrate the performance advantages of our approach.

The cognitive NET is coming

The Internet will break down without new biologically inspired routing. The future Internet will need smarter routing algorithms to handle diverse data flows and prevent failures. Although there are no tried-and-true solutions yet, early designs might follow an architecture like this one.

Predicting quality of experience in multimedia streaming

Measuring and predicting the users Quality of Experience (QoE) of a multimedia stream is the first step towards improving and optimizing the provision of mobile streaming services. This enables us to better understand how Quality of Service (QoS) parameters affect service quality, as it is actually perceived by the end user. Over the last years this goal has been pursued by means of subjective tests and through the analysis of the users feedback. Existing statistical techniques have lead to poor accuracy (order of 70%) and inability to evolve prediction models with the systems dynamics. In this paper, we propose a novel approach for building accurate and adaptive QoE prediction models using Machine Learning classification algorithms, trained on subjective test data. These models can be used for real-time prediction of QoE and can be efficiently integrated into online learning systems that can adapt the models according to changes in the environment. Providing high accuracy of above 90%, the classification algorithms become an indispensible component of a mobile multimedia QoE management system.

An adaptive multi-constraint partitioning algorithm for offloading in pervasive systems

Offloading is a kind of mechanism utilized in pervasive systems to leverage the severity of resource constraints of mobile devices by migrating part of the classes of a pervasive service/application to some resource-rich nearby surrogates. A pervasive service application needs to be partitioned prior to offloading. Such partitioning algorithms play a critical role in a high-performance offloading system. This paper proposes an adaptive (k+1) partitioning algorithm that partitions a given application into 1 unoffloadable partition and k offloadable partitions. Furthermore, these partitions satisfy the multiple constraints imposed by either application users or mobile device resources. Underpinning the partitioning algorithm is a dynamic multi-cost graph that models the costs of an application in terms of its component classes (including CPU cost, memory cost and communication cost), and a Heavy-Edge and Light-Vertex Matching (HELVM) algorithm to coarsen the multi-cost graph. An offloading toolkit implementing the above algorithms has been developed, upon which the evaluations are carried out. The outcomes of the evaluation have indicated a higher level of performance of our algorithm in terms of its efficiency and cost-effectiveness

Addressing user expectations in mobile content delivery

Multimedia services like television programs and live streaming of mobile videos can be delivered to mobile terminals via different access technologies. The question is - how do users perceive such services on mobile terminals? The objective of this study is to find the correlation between video quality thresholds and the user context. Our study reveals the thresholds of users quality of experience (QoE) in a mobile environment by using different categories of content types, in relation to different access technologies and terminal capability. The mobile terminals used are: - (i) 3G Mobile Phone (ii) Personal Digital Assistant (PDA) and (iii) Laptop. We argue that quality of service (QoS) management should be driven by the user perception of quality rather than resulting from raw engineering parameters such as latency, jitter, bandwidth etc. Our results will be of great interest to network operators, service providers, terminal manufacturers, and researchers working in the area of quality of service management.

Modelling network and system monitoring over the Internet with mobile agents

Distributed Network Management is gaining importance due to the explosive growth of the size of computer networks. New management paradigms are being proposed as an alternative to the centralised one, and new technologies and programming languages are making them feasible. The use of Mobile Agents (MAs) to distribute and delegate management tasks is a particularly promising approach to dealing with the limitations of current centralised management systems which appear to be lacking flexibility and scalability. This paper is focused on the impact that mobile code paradigms can have on distributed network and system monitoring. A dynamic, hierarchical management model based on a delegation paradigm is adopted and an MA-architecture for monitoring operations is proposed. Finally, possible uses of the proposed model and architecture for pursuing seamless and timely monitoring are discussed.

The Operator's Response to P2P Service Demand

Peer-to-peer (P2P) systems are in high demand for all sorts of tasks-video communication, resource sharing, and content retrieval, to mention a few. However, current P2P solutions are intrinsically incompatible with the IP multimedia subsystem (IMS), the service provisioning framework adopted by the major telecommunication players. We look at ways to develop P2P applications over IMS, identifying the essential service components that pave the way toward interoperable P2P. We discuss the added value that a P2P-IMS solution offers to all parties involved in the service provisioning chain: content provider, third-party service provider, network operator, and ultimately, the user. P2P-IMS brings the power of P2P (increased scalability, availability, resilience, and resource utilization) to the future domain of services, creating a wealth of new business opportunities. Our findings are supported by an IMS-compliant prototype, including a variety of applications.