Dimitrios P. Pezaros

Deploying Rural Community Wireless Mesh Networks

Inadequate Internet access is widening the digital divide between town and countryside, degrading both social communication and business advancements in rural areas. Wireless mesh networking can provide an excellent framework for delivering broadband services to such areas. With this in mind, Lancaster University deployed a WMN in the rural village of Wray over a three-year period, providing the community with Internet service that exceeds many urban offerings. The project gave researchers a real-world testbed for exploring the technical and social issues entailed in deploying WMNs in the heart of a small community.

The Glasgow Raspberry Pi Cloud: A Scale Model for Cloud Computing Infrastructures

Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment.

Improving Data Center Network Utilization Using Near-Optimal Traffic Engineering

Equal cost multiple path (ECMP) forwarding is the most prevalent multipath routing used in data center (DC) networks today. However, it fails to exploit increased path diversity that can be provided by traffic engineering techniques through the assignment of nonuniform link weights to optimize network resource usage. To this extent, constructing a routing algorithm that provides path diversity over nonuniform link weights (i.e., unequal cost links), simplicity in path discovery and optimality in minimizing maximum link utilization (MLU) is nontrivial. In this paper, we have implemented and evaluated the Penalizing Exponential Flow-spliTing (PEFT) algorithm in a cloud DC environment based on two dominant topologies, canonical and fat tree. In addition, we have proposed a new cloud DC topology which, with only a marginal modification of the current canonical tree DC architecture, can further reduce MLU and increase overall network capacity utilization through PEFT routing.

Cross-Layer Peer-to-Peer Traffic Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a cross-layer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols.

Implementing Scalable, Network-Aware Virtual Machine Migration for Cloud Data Centers

Virtualization has been key to the success of Cloud Computing through the on-demand allocation of shared hardware resources to Virtual Machines (VM)s. However, the network-agnostic placement of VMs over the underlying network topology can itself be a factor of performance degradation by causing congestion at the core layers of the infrastructure where bandwidth is heavily oversubscribed. In this paper, we design and implement S-CORE, a scalable live VM migration scheme to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We evaluate S- CORE over diverse aggregate load and coordination policies. Our results show that it can achieve up to a 87% communication cost reduction with a limited number of migration rounds, and can be easily accommodated within commodity hardware and hypervisor architectures. The associated memory, CPU, and network overhead are also minimum under typical Cloud Data Center workloads.

In-line service measurements: an IPv6-based framework for traffic evaluation and network operations

The ability to measure, monitor and control the service quality experienced by network traffic is becoming increasingly important as multiple traffic types are aggregated onto IP networks. Assessing the real-time performance of the application flows is an essential requirement for network operations and service management, as well as for identifying how the different traffic types and transports interact and behave, when they are carried over the end-to-end Internet infrastructure. This paper introduces a novel measurement technique for assessing the performance of IPv6 network flows. By exploiting IPv6 extension headers, measurement triggers and the instantaneous measurement indications are carried in the same packets as the payload data itself. providing a high level of probability that the behaviour of the real user traffic flows is being observed. The measurement mechanism is applied at the network layer and provides for a generic technique able to measure any type of traffic without depending on particular transports or on specific measurement architectures. A prototype implementation of this technique is also described and evaluated by measuring performance properties of application flows over different-capacity IPv6 environments. End-to-end delay and jitter of video streams have been measured, as well as the goodput for services operating on top of reliable transport. This measurement technique can be the basis for low-overhead, scalable, transparent and reliable measurement of individual and aggregate network flows, and can be dynamically deployed where and when required in a multi-service IP environment.

Scalable Traffic-Aware Virtual Machine Management for Cloud Data Centers

Virtual Machine (VM) management is a powerful mechanism for providing elastic services over Cloud Data Centers (DC)s. At the same time, the resulting network congestion has been repeatedly reported as the main bottleneck in DCs, even when the overall resource utilization of the infrastructure remains low. However, most current VM management strategies are traffic-agnostic, while the few that are traffic-aware only concern a static initial allocation, ignore bandwidth oversubscription, or do not scale. In this paper we present S-CORE, a scalable VM migration algorithm to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We formulate the aggregate VM communication as an optimization problem and we then define a novel distributed migration scheme that iteratively adapts to dynamic traffic changes. Through extensive simulation and implementation results, we show that S-CORE achieves significant (up to 87%) communication cost reduction while incurring minimal overhead and downtime.

A survey of strategies for communication networks to protect against large-scale natural disasters

Recent natural disasters have revealed that emergency networks presently cannot disseminate the necessary disaster information, making it difficult to deploy and coordinate relief operations. These disasters have reinforced the knowledge that telecommunication networks constitute a critical infrastructure of our society, and the urgency in establishing protection mechanisms against disaster-based disruptions. Hence, it is important to have emergency networks able to maintain sustainable communication in disaster areas. Moreover, the network architecture should be designed so that network connectivity is maintained among nodes outside of the impacted area, while ensuring that services for costumers not in the affected area suffer minimal impact. As a first step towards achieving disaster resilience, the RECODIS project was formed, and its Working Group 1 members conducted a comprehensive literature survey on “strategies for communication networks to protect against large-scale natural disasters,” which is summarized in this article.

End-to-end and network-internal measurements of real-time traffic to residential users

Little performance data currently exists for streaming high-quality Internet video to residential users. Data on streaming performance will provide valuable input to the design of new protocols and applications, such as congestion control and error-correction schemes, and sizing playout buffers in video receivers. This paper presents measurements of streaming real-time UDP traffic to a number of residential users, and discusses the basic characteristics of the data.

Container-based network function virtualization for software-defined networks

Todays enterprise networks almost ubiquitously deploy middlebox services to improve in-network security and performance. Although virtualization of middleboxes attracts a significant attention, studies show that such implementations are still proprietary and deployed in a static manner at the boundaries of organisations, hindering open innovation. In this paper, we present an open framework to create, deploy and manage virtual network functions (NF)s in OpenFlow-enabled networks. We exploit container-based NFs to achieve low performance overhead, fast deployment and high reusability missing from todays NFV deployments. Through an SDN northbound API, NFs can be instantiated, traffic can be steered through the desired policy chain and applications can raise notifications. We demonstrate the systems operation through the development of exemplar NFs from common Operating System utility binaries, and we show that container-based NFV improves function instantiation time by up to 68% over existing hypervisor-based alternatives, and scales to one hundred co-located NFs while incurring sub-millisecond latency.