Software-defined networking (SDN) has introduced flexibility and ease of management in the network. SDN offers centralized and fine-grained control over the web it has become an industry trend and is adopted in various areas of communication and networking. Controllers in SDN play a pivotal role, and their performance is key to the stability and scalability of the network. This study evaluates different SDN controllers i.e., NOX, POX and RYU. The performance of the controllers is analyzed based on Quality of Service (QoS) parameters, including Flow Setup Latency, Round Trip Time (RTT), Initial Ping Delay (IPD), Jitter, Throughput, and TCP & UDP Bandwidth. Different-sized networks are simulated, by varying the number of switches in linear and tree topologies and hosts in a single topology, using Mininet SDN simulator. Our results show that the performance of RYU is very consistent and shows small variation in the performance with increasing network size and traffic loads as compared to NOX and POX.

With improvements in computation and storage resources, data access through the network becomes the bottleneck for several cloud applications. Even with high-speed networks, the high latency of the cloud access makes it unfeasible or un-favourable for latency-sensitive applications such as autonomous driving, smart factories, and video streaming. Edge computing provides a solution by utilizing the network edge resources that are closer to the end users. Nevertheless, it is a non-trivial task to design a large-scale edge-capable system that is stable, fault-tolerant, and efficient [1]. In this paper, present the design of EdgeKV: a novel general-purpose distributed key-value store for the network edge. We demonstrate the features of EdgeKV for achieving high efficiency and scalability while providing flexibility, ease of use, and data privacy. We evaluated our prototype on the Grid'5000 framework with multiple realistic Yahoo! Cloud Serving Benchmark (YCSB) workloads. Our initial results show that EdgeKV achieves 72% higher throughput and 47% lower latency on average than centralized cloud storage, for read-dominated workloads.

In service-oriented environments and distributed systems, service composition allows simple services to be dynamically combined into new, more complex services. Service composition techniques are usually designed as an extension to service discovery. Traditional techniques try to match a user’s requirements, often complex, with the available services. However, one-to-one matching is inefficient; it is preferable to meet the request from available services even when one of the basic services is not present. Separating composition and discovery has also led to inefficiency, especially in a highly dynamic environment. With the heterogeneity of networks, users, and applications having multiple sources, constructing service-specific overlays in large distributed networks is challenging. In this article, we propose a new service composition algorithm to deal with the problem of composing multiple autonomic elements to achieve system-wide goals. Using a self-organizing approach, autonomic entities are dynamically and seamlessly composed into service-specific overlay networks. The algorithm combines composition and service discovery into one step, thereby achieving more efficiency and less latency. The decentralized and self-organizing nature of the algorithm allows it to respond rapidly to system changes. Extensive simulation results validate the effectiveness of the approach when it is compared to other solutions.

This paper proposes a new fault-resilient service overlay for MediaPort resource discovery that allows services to be efficiently and accurately located. MediaPorts are network-side functions used in the path between the source (media server) and the sink (media client). MediaPorts enable the adaptation of media content by providing value-added services such as caching, synchronization, and special routing functions. Our new approach addresses the problems of inefficiency and large message overhead, both typical of traditional approaches to resource discovery. The approach is based on a widely studied family of chordal rings, called the optimal chordal ring. Our solution is based on the types of services offered and also on the geographical locations of nodes. Extensive simulation results are presented to validate the effectiveness of the new approach, when compared to several other service-discovery solutions.

Overlay management systems face the challenges of increased complexity and heterogeneity because of the many elements involved in providing overlay services. In dynamic networks, the challenge and complexity is increased. Service composition allows simple services to be dynamically combined into more complex services in order to provide new services. In this paper, we deal with the problem of composing multiple autonomic elements to achieve system wide goals. Using a self-organizing approach, autonomic entities are dynamically and seamlessly composed into service-specific overlay networks. The paper describes and discusses the details of the composition approach. Results of extensive simulation are presented.

This paper proposes a context-aware policy-based architecture that automates the management of overlay networks. The objective of this architecture is to form a policy layer above the overlay layer. The policy layer consists of a set of overlay policy enforcement points and an overlay policy decision point that cooperate to dynamically adapt the behavior of the overlay network to the preferences of the user, the network and the service providers. With this contribution to overlay networks, policies are generated dynamically at run time from the available context information and enforced on the fly. This paper describes our novel architecture, its advantages, and the simulation results that varify its effectiveness.