William Donnelly

Towards autonomic management of communications networks

As communications networks become increasingly dynamic, heterogeneous, less reliable, and larger in scale, it becomes difficult, if not impossible, to effectively manage these networks using traditional approaches that rely on human monitoring and intervention to ensure they operate within desired bounds. Researchers and practitioners are pursuing the vision of autonomic network management, which we view as the capability of network entities to self-govern their behavior within the constraints of business goals that the network as a whole seeks to achieve. However, applying autonomic principles to network management is challenging for a number of reasons, including: (1) A means is required to enable business rules to determine the set of resources and/or services to be provided. (2) Contextual changes in the network must be sensed and interpreted, because new management policies may be required when context changes. (3) As context changes, it may be necessary to adapt the management control loops that are used to ensure that system functionality adapts to meet changing user requirements, business goals, and environmental conditions. (4) A means is required to verify modeled data and to add new data dynamically so that the system can learn and reason about itself and its environment. This article provides an introduction to the FOCALE autonomic network management architecture, which is designed to address these challenges.

Biologically inspired self-governance and self-organisation for autonomic networks

The current complexity of network management has helped drive the need for autonomic capabilities. The vision of autonomic network management provides the ability for network devices to cooperatively self-organise and self-govern in the support of high level business goals. These principles are inspired by biological systems. In this paper, we propose key self-organisation and self-governance techniques that are drawn from principles of molecular biology including (i) blood glucose homeostasis, (ii) reaction diffusion like principles, (iii) microorganism mobility using chemotaxis techniques, and (iv) hormone signaling. Preliminary simulation results have also been presented to validate our model.

Challenges for federated, autonomic network management in the Future Internet

Regardless of which networking protocols or technologies form the core of the Future Internet it is clear that the environment as a whole will need to support a very broad range of business and user interaction modes. In todays Internet we observe the growing trend for services to be both provided and consumed by loosely coupled value networks of consumers, providers and combined consumer/providers. In this paper we argue that this trend has major implications for network management in the Future Internet. In particular, we discuss six research challenges that we believe need to be addressed by the network management community if the potential for the Future Internet to flexibly support value networks is to be realized.

An Evaluation of Parameterized Gradient Based Routing With QoE Monitoring for Multiple IPTV Providers

Future communication networks will be faced with increasing and variable traffic demand, due largely to various services introduced on the Internet. One particular service that will greatly impact resource management of future communication networks is IPTV, which aims to provide users with a multitude of multimedia services (e.g. HD and SD) for both live and on demand streaming. The impact of this will be higher, when we consider multiple IPTV services overlaid on the same network. In this paper we propose a resource management scheme for a network provider that supports multiple IPTV providers. The proposed solution incorporates a new distributed routing mechanism in the underlying network that incorporates QoE monitoring. Through this monitoring process, network providers are able to provide timely updates of quality of flows for each IPTV provider. Simulation work has been conducted to validate the efficiency of the proposed solution in comparison to standard approaches.

Dynamic Optimization Solution for Green Service Migration in Data Centres

While many aspects of the Future Internet are uncertain, one thing that is clear is that service demand will continue to rise. Also, advances in mobile devices and service technology will almost certainly cause service usage patterns to vary considerably. Another issue that the Future Internet community must be acutely aware of is the huge movement towards more sustainable forms of computing and communications technology. With the recent attention that has been put on IT energy consumption (data-centres in particular), all computing and communications systems need to consider their environmental impact from the outset. With that in mind, we propose a solution for determining the optimal placement of services in data-centre network, in order to maximize the overall renewable energy usage and minimize the cooling energy consumption. We then perform a series of experiments in order to evaluate our solution, incorporating dynamic service request profiles and actual weather and renewable energy production values.

Synthetic protocols for nano sensor transmitting platforms using enzyme and DNA based computing

Abstract The ability to create communication networks of biological nanoscale devices has the potential to open up new opportunities and applications, particularly in areas such as health care and information processing. Inspired by recent developments in molecular communication and biomolecular computing, we present in this paper a biological cell based molecular communication transmitting platform using synthetic molecular computing techniques. We investigated two protocol solutions which include DNA based computing coupled with viral particles and enzyme based computing coupled with calcium signaling. Each of these solutions is designed for different applications and environments. For each of these approaches we demonstrate how elements from various layers in the communication stack are developed using the molecular computing mechanisms. Simulation results are also presented to illustrate the functionality and performance of each solution.

Precision Farming: Sensor Analytics

The role of wireless sensor networks (WSNs) in agriculture has become prominent as part of the precision farming initiative. In the future, multiple WSN systems will be deployed on every farm. Accurate and timely analyses of the data collected by these systems will become paramount for increasing efficiency and sustainability of farming. Conventionally, analyzing monitoring data is considered to be beyond WSN capabilities, and, therefore, carried out remotely. Meanwhile, in recent years, complexity of the tasks performed by WSNs has been constantly increasing. Modern wireless sensors possess computational capacity sufficient for certain data-analytics functionality. This article overviews modern WSN functionality that incorporates a certain level of intelligence, while the authors explore challenges and potential benefits of WSN-based analytics in the scope of precision farming.

BiRSM: bio-inspired resource self-management for all IP-networks

The increased complexity of communication systems has led to new challenges in network management and more specifically, efficient mechanisms to manage communication resources. The vision of autonomic networking aims to overcome these challenges by incorporating self-governance into communication network devices, in order to improve overall efficiency and minimize human intervention. Since biological systems exhibit properties that meet the requirements of self-governance, this article proposes a bio-inspired approach to efficiently manage resources in IP based core networks, called Bio-Inspired Resource Self-Management. The approach aims to provide a holistic solution for ISPs to manage their resources at different timescales as well as automating the interactions with underlying carrier network operators for dynamic resource provisioning. The implemented solution, in a simulator, has shown improved performance compared to traditional approaches.

Adaptive Dynamic Routing Supporting Service Management for Future Internet

There is currently much debate in defining what form the Future Internet will take [22, 23, 24]. The current Internet is struggling to meet the needs of an ever-evolving society. This is largely due to the Internet now become a thriving marketplace with services at the core. The range, number and complexity of services are set to increase with an even more dynamic service environment envisioned in the future. However, as these services grow, service composition will become an important feature of the service environment, leading to new challenges in service discovery and composition mechanisms. At the same time, dynamic service environments will also require that the underlying infrastructure networks are flexible enough to handle the changing service landscape. One area this is particularly important is in dynamic routing to deal with highly dynamic and frequent service changes. In this paper, we adopt mechanisms from biology and apply these to the problems identified, resulting in an integrated Bio-inspired service management and dynamic routing solution for Future Internet. We demonstrate how the bio-inspired mechanisms not only improve each problem individually, but through their integration also improve overall network performance. Simulation results are presented to validate the proposed solution.

Policy-constrained bio-inspired processes for autonomic route management

Autonomic networking systems must be designed to achieve an appropriate balance between the operation of decentralized algorithms and processes that seek to maintain optimal or near-optimal behavior in terms of global stability, improved performance and adaptability, robustness and security, with the requirement for top-down control of the system by humans to ensure business goals are met. Taking a communications networking survivability case study, we show how the operation of decentralized algorithms, inspired by the operation of biological systems, can be controlled and constrained through the deployment of management policies authored by network administrators. We present survivability-related routing algorithms (inspired by chemotaxis, reaction-diffusion and quorum sensing biological processes) which work together to effectively reconfigure network resources when transient link failures occur and demonstrate how these algorithms can be re-parameterized via policies to improve performance given prevailing network conditions. Simulation results show how the combined operation of these algorithms, as controlled by policies, allows the network to react well to survive link failure events.