Which economic model for a water-efficient Europe? Report of a CEPS Task Force. CEPS Task Force Report, 27 November 2012

This CEPS Task Force Report focuses on how to improve water efficiency in Europe, notably in public supply, households, agriculture, energy and manufacturing as well as across sectors. It presents a number of recommendations on how to make better use of economic policy instruments to sustainably manage the EU’s water resources. Published in the run-up to the European Commission’s “Blueprint to Safeguard Europe’s Waters”, the report contributes to the policy deliberations in two ways. First, by assessing the viability of economic policy instruments, it addresses a major shortcoming that has so far prevented the 2000 EU Water Framework Directive (WFD) from becoming fully effective in practice: the lack of appropriate, coherent and effective instruments in (some) member states. Second, as the Task Force report is the result of an interactive process involving a variety of stakeholders, it is able to point to the key differences in interpreting and applying WFD principles that have led to a lack of policy coherence across the EU and to offer some pragmatic advice on moving forward

Traffic Management Applications for Stateful SDN Data Plane

The successful OpenFlow approach to Software Defined Networking (SDN) allows network programmability through a central controller able to orchestrate a set of dumb switches. However, the simple match/action abstraction of OpenFlow switches constrains the evolution of the forwarding rules to be fully managed by the controller. This can be particularly limiting for a number of applications that are affected by the delay of the slow control path, like traffic management applications. Some recent proposals are pushing toward an evolution of the OpenFlow abstraction to enable the evolution of forwarding policies directly in the data plane based on state machines and local events. In this paper, we present two traffic management applications that exploit a stateful data plane and their prototype implementation based on OpenState, an OpenFlow evolution that we recently proposed.Comment: 6 pages, 9 figure

SPIDER: Fault Resilient SDN Pipeline with Recovery Delay Guarantees

When dealing with node or link failures in Software Defined Networking (SDN), the network capability to establish an alternative path depends on controller reachability and on the round trip times (RTTs) between controller and involved switches. Moreover, current SDN data plane abstractions for failure detection (e.g. OpenFlow "Fast-failover") do not allow programmers to tweak switches' detection mechanism, thus leaving SDN operators still relying on proprietary management interfaces (when available) to achieve guaranteed detection and recovery delays. We propose SPIDER, an OpenFlow-like pipeline design that provides i) a detection mechanism based on switches' periodic link probing and ii) fast reroute of traffic flows even in case of distant failures, regardless of controller availability. SPIDER can be implemented using stateful data plane abstractions such as OpenState or Open vSwitch, and it offers guaranteed short (i.e. ms) failure detection and recovery delays, with a configurable trade off between overhead and failover responsiveness. We present here the SPIDER pipeline design, behavioral model, and analysis on flow tables' memory impact. We also implemented and experimentally validated SPIDER using OpenState (an OpenFlow 1.3 extension for stateful packet processing), showing numerical results on its performance in terms of recovery latency and packet losses.Comment: 8 page

Exploring good practice knowledge transfer related to post tsunami housing re-construction in Sri Lanka

Sri Lanka was badly affected by the tsunami that occurred on 26th December 2004. The tsunami destroyed about two-thirds of the Sri Lankan coastline and affected more than 1,000,000 people. It does not only affected the lives of the community, but also had a devastating effect on their housing and livelihoods. The overall loss of 100,000 or more houses due to the tsunami proved to be a major challenge to the emergency response teams and disaster planners. Although several major disasters of varying magnitudes have occurred in the world, the body of knowledge related to post-disaster housing reconstruction and rehabilitation appears fragmented and poorly integrated. This paper attempts to fill this theoretical gap by focusing on the extent to which good practice knowledge transfer helps in overcoming this problem for more effective and efficient delivery of post-tsunami housing in Sri Lanka. The paper applied knowledge transfer principles within the context of the two housing reconstruction strategies employed in post-tsunami housing reconstruction in Sri Lanka; namely donor-driven housing and owner driven housing. The results of this study reveal that the knowledge transfer within this context cannot be simply copied and inserted from one context without any localisation. Therefore, the paper proposes a high-level abstraction of the core principles of community engagement through participatory techniques associated with appropriate capacity and capability building techniques that will enable the various stakeholders to create a new application to suit the appropriate context of the transfer destination (post-tsunami context in Sri Lanka)

Cyber security investigation for Raspberry Pi devices

Big Data on Cloud application is growing rapidly. When the cloud is attacked, the investigation relies on digital forensics evidence. This paper proposed the data collection via Raspberry Pi devices, in a healthcare situation. The significance of this work is that could be expanded into a digital device array that takes big data security issues into account. There are many potential impacts in health area. The field of Digital Forensics Science has been tagged as a reactive science by some who believe research and study in the field often arise as a result of the need to respond to event which brought about the needs for investigation; this work was carried as a proactive research that will add knowledge to the field of Digital Forensic Science. The Raspberry Pi is a cost-effective, pocket sized computer that has gained global recognition since its development in 2008; with the wide spread usage of the device for different computing purposes. Raspberry Pi can potentially be a cyber security device, which can relate with forensics investigation in the near future. This work has used a systematic approach to study the structure and operation of the device and has established security issues that the widespread usage of the device can pose, such as health or smart city. Furthermore, its evidential information applied in security will be useful in the event that the device becomes a subject of digital forensic investigation in the foreseeable future. In healthcare system, PII (personal identifiable information) is a very important issue. When Raspberry Pi plays a processor role, its security is vital; consequently, digital forensics investigation on the Raspberry Pies becomes necessary