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Panagiotis Kokkinos describes a case of acute feline paraparesis he saw when working as a rotating intern at the Centre of Small Animal Studies, Animal Health Trust.

The uncertain and non-dispatchable nature of renewable energy sources renders Demand Response (DR) a critical component of modern electricity distribution systems. Demand Response (DR) service provision takes place via aggregators and special distribution-level markets (e.g., flexibility markets), where small, distributed DR resources, such as building energy management systems, electric vehicle charging stations, micro-generation and storage, connected to the low-voltage distribution grid, offer DR services. In such systems, energy balancing (and thus, also DR decisions) have to be made close to real-time. Thus, market clearing algorithms for DR service provision must fulfill several requirements related to the efficiency of their operation. More specifically, a DR market clearing algorithm needs to be optimal in terms of cost-efficiency, scalable in terms of number of assets and locations, and able to satisfy real-time constraints. In order to cope with these challenges, this paper presents a distributed DR market clearing algorithm based on Lagrangian decomposition, combined with an optimal cloud resource allocation algorithm for assigning the required computation power. A heuristic algorithm is also presented, able to achieve a near-optimal solution, within negligible computational time. Simulations, performed on a testbed, demonstrate the computational burden introduced by various DR models, as well as the heuristic algorithm's near-optimal performance. The resource allocation algorithm is able to service multiple DR requests (e.g. in multiple distribution networks), and minimize the cost of computational resources while respecting the execution time constraints of each request. This enables third parties to offer cost-efficient and competitive DR operation as a service.

We present the Disaster Recovery Layer (DRL) that enables OpenStack-managed datacenter workloads, Virtual Machines (VMs) and Volumes, to be protected and recovered in another datacenter, in case of a disaster. This work has been carried out in the context of the EU FP7 ORBIT project that develops technologies for enabling business continuity as a service. The DRL framework is based on a number of autonomous components and extensions of OpenStack modules, while its functionalities are available through OpenStack's Horizon UI and command line interface. Also, the DRL's architecture is extensible, allowing for the easy and dynamic integration of protection, restoration and orchestration plug-ins that adopt new approaches. A distributed disaster detection mechanism was also developed for identifying datacenter disasters and alerting the DRL. For the evaluation of the DRL, a two (active and backup) datacenters testbed has been setup in respective sites in Umea and Lulea, 265km apart and connected through the Swedish national research and education network. In case of a disaster, traffic is redirected between the datacenters utilizing the BGP anycast scheme. The experiments performed, show that DRL can efficiently protect VMs and Volumes, with minimum service disruption in case of failures and low overhead, even when the available bandwidth is limited.

We present a self-configured and unified access and metro network architecture, named ARMONIA. The ARMONIA network monitors its status, and dynamically (re-)optimizes its configuration. ARMONIA leverages software defined networking (SDN) and network functions virtualization (NFV) technologies. These technologies enable the access and metro convergence and the joint and efficient control of the optical and the IP equipment used in these different network segments. Network monitoring information is collected and analyzed utilizing machine learning and big data analytics methods. Dynamic algorithms then decide how to adapt and dynamically optimize the unified network. The ARMONIA network enables unprecedented resource efficiency and provides advanced virtualization services, reducing the capital expenditures (CAPEX) and operating expenses (OPEX) and lowering the barriers for the introduction of new services. We demonstrate the benefits of the ARMONIA network in the context of dynamic resource provisioning of network slices. We observe significant spectrum and equipment savings when compared to static overprovisioning.

The number and size of megacities and their respective networking and computing infrastructures constantly increases, while a large part of the network traffic originates and terminates locally. In such a dense and heterogeneous environment, network slices are formed, utilizing various optical networking infrastructures that carry data from end users to distributed, intra-city edge computing units, in which applications' workload is appropriately offloaded. In our work, we examine mechanisms for the joint resource allocation and the applications' workload placement in the access and metro network segments.

Objective: To determine contamination rates of scrub suits worn by veterinary surgeons and nurses following a single shift. Methods: Cross sectional pilot study. Sterilised scrub suits were distributed to veterinary surgeons (n = 9) and nurses (n = 9) at the beginning of their clinical shift and worn for at least 8 hours, at a UK small animal referral center. Microbiological analysis of the scrub suits was conducted before and after home laundry at 30ºC. A questionnaire was distributed to hospital clinical staff regarding uniform habits.Results: Median bacterial counts of 47 (interquartile range [IQR] 14 to 162) and 7 (IQR 0 to 27) colony forming units per cm2 (cfu/cm2) were present before and after laundry of scrub suits (difference: -40 cfu/cm2, p = 0.025). Bacteria identified included: Staphylococcus sp., Enterococcus sp., Escherichia coli, Bacillus sp., Pseudomonas aeruginosa, Micrococcus sp., β-haemolytic Streptococci and a Group G Streptococcus. From 101 staff surveyed, 64.0% reported wearing fresh, clean scrub tops and 58.4% fresh, clean trousers each day, while 64.4% left the workplace wearing the same clothing in which they undertook clinical work. Conclusion: Workwear contamination risks spread of pathogens into the community and staff compliance with workplace guidelines warrants further attention. Home laundry at 30 ºC significantly decreases, but does not eliminate, the bacterial burden after a single shift. Clinical significance: The significant presence of bacteria on the uniforms after the shift ended necessitates further study, particularly regarding wearing health care uniforms outside of the work environment.

Today, home appliances like air-conditions, ovens, refrigerators, and washing machines, become more and more intelligent, enabling homeowners to monitor and manage them remotely. However, the plethora of different and usually proprietary interfaces provided by the manufacturers makes it difficult to build smart home and smart city applications that involve the concurrent remote management of multiple home appliances. In this work, we categorize the basic characteristics of the available intelligent home appliances and propose YANG models that describe these characteristics. NETCONF experimental demonstrations are carried out to display the control and management capabilities of the technologies applied.

The plethora, the diversity of Internet of Things (IoT) devices and the targeted multi-domain applications, have created a complex environment for new developers to create applications. Also, the introduction of science, technology, engineering, and mathematics (STEM) courses, starting from the elementary school, it is not just a trend anymore but an important part of the educational curriculum. Usually, however, the platforms used in these STEM courses, like Arduino, Raspberry Pi and others, lack any capabilities for central or distributed coordination between the involved devices. In our work, we present OpenMIC library for the development of multi-agent applications running in several devices, providing intelligence and computing capabilities. We discuss the architecture and the implementation details of the OpenMIC library and describe how new applications based on the OpenMIC library can be developed. An example application is also presented for the monitoring and the management of multiple IoT devices.

Hypervisors' smooth operation and efficient performance has an immediate effect in the supported Cloud services. We investigate scheduling algorithms that match I/O requests originated from virtual resources, to the physical CPUs that do the actual processing. We envisage a new paradigm of virtualized resource consolidation, where I/O resources required by several Virtual Machines (VMs) in different physical hosts, are provided by one (or more) external powerful dedicated appliance(s), namely the I/O Hypervisor (IOH). For this reason I/O operations are transferred from the VMs to the IOH, where they are executed. We propose and evaluate a number of scheduling algorithms for this hypervisor model, concentrating on providing guaranteed fairness among the virtual resources. A simulator has been built that describes this model and is used for the implementation and the evaluation of the algorithms. We also analyze the performance of the different hypervisor models and highlight the importance of fair scheduling.

We present a hierarchical orchestration platform for inter-domain datacenter networks that includes hybrid optical-electrical intra-datacenter networking and inter-datacenter networking utilizing elastic technologies. We demonstrate dynamic and joint allocation of capacity in an emulated testbed.

We present an admission control and solution validation-based online, routing, spectrum allocation approach for elastic optical networks. This is parameterized periodically by an optimal offline mechanism that drives the blocking of traffic requests, which if served would negatively affect network performance.

The recent developments in network programmability and flexibility, shape the environment for the creation and offering of networking capacity services. Through such services one will be able to reserve on demand raw network capacity and for a specific duration, in the form of virtual links or of virtual networks that interconnect branch offices, datacenters or devices around the world. In this work, we initially present the capacity services landscape as it is formulated and discuss on the relations with the cloud computing service model. Next, we propose optimal Integer Linear Programming (ILP) based mechanisms for matching network demands to networking capacity services, in the same way users’ computing requirements can be matched to virtual computing instances. We show through simulations that the proposed mechanisms can optimize the bandwidth usage, while minimizing the cost associated with the use of the network resources. We also investigate the effects of malleable capacity requests and of dynamic pricing.

Energy consumption and the associated costs constitute a crucial issue concerning the design and operation of data networks and data centers. Energy-awareness is required in all levels, ranging from physical layer to algorithms, protocols and applications. Architecture-wise, a promising solution for tackling the increasing energy requirements is the deployment of optics at both long and shorter distances, including within data centers. Vertical Cavity Surface Emitting Lasers (VCSEL) constitute a popular photonic transmitter technology used in numerous short-range applications, providing also the ability to reduce energy consumption by scaling down the transmission bit rate. In this study we focus on the algorithmic aspects of energy management by proposing an OptiMal EnerGy Aware (OMEGA) routing algorithm to operate in optical networks utilizing VCSEL-based opto-electronic links. The algorithm leverages the capability of VCSELs to adapt the energy dissipation with respect to the transmission bit rate. Simulation results, under various traffic patterns, show that OMEGA balances efficiently the traffic load over the network's links, resulting in high throughput and low energy consumption.

A 3-year-old female spayed dog was presented with a history of sanguineous vaginal discharge of 2 month duration. The dog was spayed 1.5 years before presentation. Clinical examination revealed a large, solid, ovoid mass in the caudal abdomen, recognized by diagnostic imaging as an enlargement at the top of the uterine stump. Additionally, high serum progesterone concentration was measured, confirming the presence of functional ovarian tissue in dioestrus. With a suspicion for a related uterine stump pyometra or less likely, for other enlargements, a cοeliotomy was performed. A mass at the apex of the uterine body and a right side ovarian remnant were found. Both structures and the remaining uterine stump were excised. The uterine remnant mass was histologically diagnosed as uterine adenocarcinoma, herein detected for the first time at the uterine stump in the bitch. Unsuccessful, incomplete ovariohysterectomy may permit even neoplastic transformation of uterine stump tissues.

Resource selection and task assignment are basic operations in distributed computing environments, like the grid and the cloud, where tasks compete for resources. The decisions made by the corresponding algorithms should be judged based not only on metrics related to user satisfaction, such as the percentage of tasks served without violating their quality-of-service (QoS) requirements, but also based on resource-related performance metrics, such as the number of resources used to serve the tasks and their utilization efficiency. In our work, we focus on the case of tasks with fixed but not strict time requirements, given in the form of a requested start and finish time. We propose an algorithm for assigning tasks to resources that minimizes the violations of the tasks' time requirements while simultaneously maximizing the resources' utilization efficiency for a given number of resources. The exact time scheduling of the tasks on the resources is then decided by taking into account the time constraints. The proposed scheme exploits concepts derived from graph partitioning, and groups together tasks so as to 1) minimize the time overlapping of the tasks assigned to a given resource and 2) maximize the time overlapping among tasks assigned to different resources. The partitioning is performed using a spectral clustering methodology through normalized cuts. Experimental results show that the proposed algorithm outperforms other scheduling algorithms for different values of the granularity and the load of the task requests.

We discuss the basic algorithmic issues in planning and operating flexible optical networks, highlighting the challenges and differences from fixed-grid WDM networks. We also overview commercially available planning and operation tools, which (expectedly) lack support for flexible optical networks at the moment, as flexible technologies are not yet deployed in real networks. To fill this need we present the Mantis tool. Mantis' modular architecture provides fast running times, efficient and fault-tolerant usage of computation resources, and execution as both a desktop application and a cloud software-as-a-service.

We propose new burst assembly schemes and fast reservation (FR) protocols for Optical Burst Switched (OBS) networks that are based on traffic prediction. The burst assembly schemes aim at minimizing (for a given burst size) the average delay of the packets incurred during the burst assembly process, while the fast reservation protocols aim at further reducing the end-to-end delay of the data bursts. The burst assembly techniques use a linear prediction filter to estimate the number of packet arrivals at the ingress node in the following interval, and launch a new burst into the network when a certain criterion, different for each proposed scheme, is met. The fast reservation protocols use prediction filters to estimate the expected length of the burst and the time needed for the burst assembly process to complete. A Burst Header Packet (BHP) packet carrying these estimates is sent before the burst is completed, in order to reserve bandwidth at intermediate nodes for the time interval the burst is expected to pass from these nodes. Reducing the packet aggregation delay and the time required to perform the reservations, reduces the total time needed for a packet to be transported over an OBS network and is especially important for real-time applications. We evaluate the performance of the proposed burst assembly schemes and show that a number of them outperform the previously proposed timer-based, length-based and average delay-based burst assembly schemes. We also look at the performance of the fast reservation (FR) protocols in terms of the probability of successfully establishing the reservations required to transport the burst.

The availability of cloud applications and their respective server high availability is affected by inefficient load balancing configurations, denial of service attacks (DoS), link failures, power outages etc. As these issues may never disappear, traffic redirection from the affected server to a backup one is an important procedure followed for restoring the provided service. In this work, we initially evaluate a reverse proxy server-based scheme for traffic redirection, using High Availability proxy server(HAproxy) and also we develop a Software Defined Network (SDN)-based solution. We compare the proxy server-based and the SDN-based schemes, exhibiting how each can be used to mitigate downtime in case of a failure, providing high availability.

Dynamic optical networking allows operators to effectively maximize the capacity of their physical infrastructure and cope with the rapid growth rates of the Internet traffic. In the framework of the European DICONET project we proposed and developed a comprehensive solution that utilizes the dynamicity as well as the valuable physical layer information of a reconfigurable WDM core network to provide a smooth transition from the quasi-static networking of today to an intelligent reconfigurable and physical impairment-aware architecture. In this work we discuss the benefits of implementing the DICONET solution and present some of the major achievements of the project that support both the planning and operation phase of a core optical network.

The impact of physical layer impairments in the planning and operation of all-optical (and translucent) networks is the consideration of the DICONET project. The impairment-aware network planning and operation tool (NPOT) is the main outcome of the DICONET project, and is explained in detail in this paper. We describe the key building blocks of NPOT, consisting of the network description repositories, the physical layer performance evaluator, the impairment-aware routing and wavelength assignment (IA-RWA) engines, the component placement modules, the failure handling and the integration of NPOT in the control plane. Also, we present several experimental results for NPOT, evaluating the performance of its IA-RWA engines.

We propose a class of novel energy-efficient multi-cost routing algorithms for wireless mesh networks, and evaluate their performance. In multi-cost routing, a vector of cost parameters is assigned to each network link, from which the cost vectors of candidate paths are calculated using appropriate operators. In the end these parameters are combined in various optimization functions, corresponding to different routing algorithms, for selecting the optimal path. We evaluate the performance of the proposed energy-aware multi-cost routing algorithms under two models. In the network evacuation model, the network starts with a number of packets that have to be transmitted and an amount of energy per node, and the objective is to serve the packets in the smallest number of steps, or serve as many packets as possible before the energy is depleted. In the dynamic one-to-one communication model, new data packets are generated continuously and nodes are capable of recharging their energy periodically, over an infinite time horizon, and we are interested in the maximum achievable steady-state throughput, the packet delay, and the energy consumption. Our results show that energy-aware multi-cost routing increases the lifetime of the network and achieves better overall network performance than other approaches. Copyright © 2011 John Wiley & Sons, Ltd.

We examine a task scheduling and data migration problem for grid networks, which we refer to as the Data Consolidation (DC) problem. DC arises when a task concurrently requests multiple pieces of data, possibly scattered throughout the grid network, that have to be present at a selected site before the task's execution starts. In such a case, the scheduler and the data manager must select (i) the data replicas to be used, (ii) the site where these data will be gathered for the task to be executed, and (iii) the routing paths to be followed; this is assuming that the selected datasets are transferred concurrently to the execution site. The algorithms or policies for selecting the data replicas, the data consolidating site and the corresponding paths comprise a Data Consolidation scheme. We propose and experimentally evaluate several DC schemes of polynomial number of operations that attempt to estimate the cost of the concurrent data transfers, to avoid congestion that may appear due to these transfers and to provide fault tolerance. Our simulation results strengthen our belief that DC is an important problem that needs to be addressed in the design of data grids, and can lead, if performed efficiently, to significant benefits in terms of task delay, network load and other performance parameters.

Hyperscale datacenters (DCs), spread in various locations around the globe, provide computing and storage resources for cloud and other applications. Elastic optical networks (both landline and subsea) operated by a single or multiple entities are used to form the inter-DC network and serve the constantly increasing traffic. In addition, optical switching technologies are researched for intra-DC networks as a means to achieve higher capacity and energy efficiency. Joint optimization and orchestration of inter-DC and intra-DC network infrastructures is the key for realizing the network virtualization and network as service visions. We present a hierarchical software defined networking orchestration platform that treats intra-DC and inter-DC networks as domains and cooperates with domain specific orchestrators/controllers to achieve interdomain, end-to-end orchestration. The systems developed are evaluated both in an emulated and in a realistic testbed, showcasing dynamic end-to-end path establishment functionality with dedicated capacity and low control overhead.

In this work we study the combination of multi-cost routing and adjustable transmission power in wireless ad hoc networks, so as to obtain dynamic energy- and interference-efficient routes to optimize network performance. In multi-cost routing, a vector of cost parameters is assigned to each network link, from which the cost vectors of candidate paths are calculated. Only at the end these parameters are combined in various optimization functions, corresponding to different routing algorithms, for selecting the optimal path. The multi-cost routing problem is a generalization of the multi-constrained problem, where no constraints exist, and is also significantly more powerful than single-cost routing. Since energy is an important limitation of wireless communications, the cost parameters considered are the number of hops, the interference caused, the residual energy and the transmission power of the nodes on the path; other parameters could also be included, as desired. We assume that nodes can use power control to adjust their transmission power to the desired level. The experiments conducted show that the combination of multi-cost routing and adjustable transmission power can lead to reduced interference and energy consumption, improving network performance and lifetime.

In translucent (or managed reach) WDM optical networks, regenerators are employed at specific nodes. Some of the connections in such networks are routed transparently, while others have to go through a sequence of 3R regenerators that serve as ?refueling stations? to restore their quality of transmission (QoT). We extend an online multicost algorithm for transparent networks presented in our previous study, to obtain an IA-RWA algorithm that works in translucent networks and makes use, when required, of the regenerators present at certain locations of the network. To characterize a path, the algorithm uses a multicost formulation with several cost parameters, including the set of available wavelengths, the length of the path, the number of regenerators used, and noise variance parameters that account for the physical layer impairments. Given a new connection request and the current utilization state of the network, the algorithm calculates a set of non dominated candidate paths, meaning that any path in this set is not inferior with respect to all cost parameters than any other path. This set consists of all the cost-effective (in terms of the domination relation) and feasible (in terms of QoT) lightpaths for the given source-destination pair, including all the possible combinations for the utilization of available regenerators of the network. An optimization function or policy is then applied to this set in order to select the optimal lightpath. Different optimization policies correspond to different IA-RWA algorithms. We propose and evaluate several optimization policies, such as the most used wavelength, the best quality of transmission, the least regeneration usage, or a combination of these rules. Our results indicate that in a translucent network the employed IA-RWA algorithm has to consider all problem parameters, namely, the QoT of the lightpaths, the utilization of wavelengths and the availability of regenerators, to efficiently serve the online traffic.

We present and theoretically and experimentally analyze a Quality of Service (QoS) framework for Grids that provides (i) deterministic delay bounds to Guaranteed Service (GS) users and (ii) fair sharing of resources to Best Effort (BE) users. The framework adopts concepts from Data Networks and applies them in the Grid environment. We initially describe the proposed framework assuming that task computational workloads are known (or can be estimated), and then provide extensions for the more realistic case where we have no a-priori knowledge of the task workloads. Task migration across multiple resources is also examined in this context. We also look at a specific implementation of the proposed QoS scheme, where we distinguish computational resources, based on the type of users (GS or BE) they serve and the priority they give to each type. We validate experimentally the proposed QoS framework for Grids, verifying that it satisfies the delay guarantees promised to GS users and provides fairness among BE users, while simultaneously improving performance in terms of deadlines missed and resource utilization. In our simulations, data from a real Grid Network are used.

Hypervisors' smooth operation and efficient performance has an immediate effect in the supported Cloud services. We investigate scheduling algorithms that match I/O requests originated from virtual resources, to the physical CPUs that do the actual processing. We envisage a new paradigm of virtualized resource consolidation, where I/O resources required by several Virtual Machines (VMs) in different physical hosts, are provided by one (or more) external powerful dedicated appliance(s), namely the I/O Hypervisor (IOH). For this reason I/O operations are transferred from the VMs to the IOH, where they are executed. We propose and evaluate a number of scheduling algorithms for this hypervisor model, concentrating on providing guaranteed fairness among the virtual resources. A simulator has been built that describes this model and is used for the implementation and the evaluation of the algorithms. We also analyze the performance of the different hypervisor models and highlight the importance of fair scheduling.

Background Reducing energy consumption and CO2 emissions in order to address climate change requires behavioral changes by the citizens, who will have to adopt more environmentally friendly and energy-saving practices. Methods We present a system and corresponding practices for gathering energy consumption data from public school buildings over the Internet, processing them to identify hidden correlations and produce actionable advice and presenting the results in real-time to its occupants over the Web. We describe the metering infrastructure installed at schools for energy consumption monitoring and the related actions carried out in order to motivate local school communities towards an environmentally friendly behavior. The introduction of IPv6 was found to be a key enabling technology for setting up such a system in a simple, secure, and efficient way. Results The proposed system and processes are put under test in a pilot installation composed of about 50 IPv6-enabled schools of the Greek School Network (GSN). These are also combined with appropriate educational and social engagement tools. In this way, energy consumption, operating costs, and greenhouse effects can be reduced in the area of educational and public administration buildings in general. Thus, people become almost instantly aware of the energy and environmental implications of their actions, which motivates them towards behavioral changes and the adoption of environmentally friendly practices. Conclusions The pilot provides a good example of collaboration between the ICT sector, the smart building and automation vendors, and the public authorities.

Cloud computing and virtualized infrastructures are currently the baseline environments for the provision of services in different application domains. While the number of service consumers increasingly grows, service providers aim at exploiting infrastructures that enable non-disruptive service provisioning, thus minimizing or even eliminating downtime. Nonetheless, to achieve the latter current approaches are either application-specific or cost inefficient, requiring the use of dedicated hardware. In this paper we present the reference architecture of a fault-tolerance scheme, which not only enhances cloud environments with the aforementioned capabilities but also achieves high-performance as required by mission critical every day applications. To realize the proposed approach, a new paradigm for memory and I/O externalization and consolidation is introduced, while current implementation references are also provided.

An optical network, like any system, has to be observable before it can become subject to optimization, and this is the main capability that ORCHESTRA project introduces. ORCHESTRA's high observability will rely on information provided by the coherent transceivers that can be extended, almost for free, to operate as software defined optical performance monitors (soft-OPM). Novel digital signal processing (DSP) OPM algorithms will be developed and combined with a novel hierarchical monitoring plane, cross-layer optimization algorithms and active-control functionalities. ORCHESTRA vision is to close the control loop, enabling true network dynamicity and unprecedented network capacity efficiency.

Optical interconnection networks are being used in systems on chip, supercomputers, and datacenters, fueling exascale computing, big data, and artificial intelligence applications. The vertical cavity surface emitting laser (VCSEL) is a popular, mature, and cost-effective photonic transmitter technology that enables energy proportionality by allowing the links’ data rate and the associated power consumption to be adjusted. Our work assumes VCSEL-based optical interconnects and presents intelligent centralized and distributed mechanisms to jointly and optimally select the routes, the flow sizes, and the transmission powers needed to serve a given input traffic load, minimize the consumed energy, and optimize performance. For this purpose, we use a detailed VCSEL energy model and formulate the energy minimization problem as a constrained nonlinear multicommodity optimization problem, which is solved optimally with the proposed approaches. The simulation results, carried out under a variety of scenarios, show the efficiency of these methods in terms of throughput and energy consumption.

We present a methodology, called communication-aware virtual infrastructures (COMAVI), for the concurrent migration of multiple Virtual Machines (VMs) in cloud computing infrastructures, which aims at the optimum use of the available computational and network resources, by capturing the interdependencies between the communicating VMs. This methodology uses multiple criteria for selecting the VMs that will migrate, with different weights assigned to each of them. COMAVI also selects the computing sites/units where the migrating VMs will be hosted, by accounting for the way migration affects the logical (or virtual) topologies formed by the communicating VMs and viewing this selection as a logical topology reconfiguration problem. COMAVI resolves the maximum possible number of VM resource shortages, while tending to minimize the number of migrations performed, the induced network overhead, the logical topology reconfigurations required, and the corresponding service interruptions. We evaluate the proposed method through simulations, where we exhibit their performance benefits.

PERIKLIS platform encourages citizen participation and supports sophistication of electronic government services by leveraging the capabilities of location based services, social networks and web 2.0 technologies. In this paper a structured analysis is adopted for identifying the advantages, from the digital transformation of the government transactions and the electoral processes, exploring the notion of society members and the benefits for better life conditions through electronic transactions in a Municipality. Adopting a computing approach for e-government and voting methodologies with an easy setup and completion by its members is investigated, reviewing the availability of services through mobile and web based systems, coupled with geo location services. Furthermore, PERIKLIS proposes a high level e-governance and e-voting solution for a municipality while investigating issues that require further research for exploitation and interoperability with more than one Municipalities.

We present a network planning and operation tool, called Mantis, for designing the next generation optical networks, supporting both flex-grid and mixed line rate networks. Through Mantis, the user is able to define the network topology the traffic matrix, the CAPEX/OPEX parameters, setup basic configuration parameters, and use a library of algorithms to plan, operate, or evaluate an optical network of interest. Mantis is designed to be deployed either as a desktop application or as a cloud service. For its execution Mantis can utilize the services of the Amazon Elastic Compute Cloud (Amazon EC2) , however its modular architecture allows other cloud services to be adopted in the future with minimum effort. Using the cloud services Mantis can scale based on the user demands, executing fast and efficiently the scenarios requested. The included planning and operation algorithms range from routing, to equipment placement and to wavelength and spectrum allocation and others.

The monitoring and the analysis of public clouds gains momentum, due to their widespread exploitation by individual users, researchers and companies for their daily tasks. We propose an algorithm for optimizing the cost and the utilization of a set of running Amazon EC2 instances by resizing them appropriately. The algorithm, namely Cost and Utilization Optimization (CUO) algorithm, receives information regarding the current set of instances used (their number, type, utilization) and proposes a new set of instances for serving the same load, so as to minimize cost and maximize utilization, or increase performance efficiency. CUO is integrated in Smart cloud Monitoring (SuMo), an open-source tool we develop for collecting monitoring data from Amazon Web Services (AWS) and analyzing them. A number of experiments are performed, using input data that correspond to realist AWS configuration scenarios, which exhibit the benefits of the CUO algorithm.

This chapter describes routing and medium access control (MAC) mechanisms for providing Quality of Service (QoS) together with energy savings in wireless ad hoc networks. The proposed mechanisms operate in a cross-layer optimization logic, in the direction of either minimizing total energy consumption in the network or maximizing network lifetime, while at the same time providing QoS to the end users. The authors present a multi-cost routing approach, where various cost parameters and optimization functions are defined and used for selecting the paths to be followed. Also, routing and MAC protocols are investigated for the case where nodes have variable transmission power capabilities. Finally, the performance of the proposed protocols is evaluated and compared to that of other well-known routing and MAC protocols.

International audience; Core optical networks using reconfigurable optical switches and tunable lasers appear to be on the road towards widespread deployment and could evolve to all-optical mesh networks in the coming future. Considering the impact of physical layer impairments in the planning and operation of all-optical (and translucent) networks is the main focus of the Dynamic Impairment Constraint Optical Networking (DICONET) project. The impairment aware network planning and operation tool (NPOT) is the main outcome of DICONET project, which is explained in detail in this paper. The key building blocks of the NPOT, consisting of network description repositories, the physical layer performance evaluator, the impairment aware routing and wavelength assignment engines, the component placement modules, failure handling, and the integration of NPOT in the control plane are the main contributions of this study. Besides, the experimental result of DICONET proposal for centralized and distributed control plane integration schemes and the performance of the failure handling in terms of restoration time is presented in this study.

In this work we discuss Fun in Numbers, a software platform for implementing multiplayer games and interactive installations, that are based on the use of ad hoc mobile sensing devices. We utilize a detailed log of a three-day long public showcase as a basis to discuss the implementation issues related to a set of games and installations, which are examples of this unique category of applications, utilizing a blend of technologies. We discuss their fundamental concepts and features, also arguing that they have many aspects and potential uses. The architecture of the platform and implementation details are highlighted in this work, along with detailed descriptions of the protocols used. Our experiments shed light on a number of key issues, such as network scaling and real-time performance, and we provide experiments regarding cross-layer software issues. We additionally provide data showing that such games and installations can be efficiently supported by our platform, with as many as 50 concurrent players in the same physical space. These results are backed up by a user evaluation study from a large sample of 136 visitors, which shows that such applications can be seriously fun.

We consider routing and wavelength assignment (RWA) in a WDM network consisting of optical cross-connect (OXC) nodes that have color and direction constraints. These restricted node architectures have a smaller cost than the more flexible (and best performing) ones usually assumed in the RWA problem. This introduces an interesting tradeoff between the network performance achieved, in terms of network blocking and number of manual interventions required, and the cost of the node architecture used. In the process of comparing the node architectures, we propose an adaptation of an RWA algorithm that accounts for the lack of node flexibility, aiming to achieve using the constrained node architectures, performance similar to that obtained with the fully flexible node architectures. Additionally, we consider different transponder assignment policies and determine their effect on performance.

—In transparent and translucent wavelength routed optical networks the signal quality degrades due to physical layer impairments while the interference among lightpaths implies that routing decisions for one lightpath affect and are affected by the decisions made for other lightpaths. To establish a lightpath for a new connection two main approaches can be used. The most common approach is to select a lightpath that has acceptable transmission quality under a worst case interference assumption, ensuring that the selected lightpath will not become infeasible due to the possible establishment of future interfering connections. This approach sacrifices candidate path space for a quick and stable lightpath selection, which is appealing from a complexity viewpoint. The second approach is to consider the current network utilization and account for the actual interference among lightpaths, performing a cross layer optimization between the network and physical layers. In this case, however, the algorithm has to check whether the establishment of the new lightpath turns infeasible some of the already established connections. The question that arises is whether the performance benefits that can be achieved through the second approach are worth the added complexity introduced by the cross-layer optimization applied.

We present a network operation tool called Impairment Aware Lightpath Computation Engine (IALCE) that incorporates an impairment-aware routing and wavelength assignment (RWA) algorithm. We perform experiments illustrating the flexibility of the engine and the performance of the algorithm.

We consider path protection in the routing and wavelength assignment (RWA) problem for impairment constrained WDM optical networks. The proposed multicost RWA algorithms select the primary and the backup lightpaths by accounting for physical layer impairments. The backup lightpath may either be activated (1+1 protection) or it may be reserved and not activated, with activation taking place when/if needed (1:1 protection). In case of 1:1 protection the period of time where the quality of its transmission (QoT) is valid, despite the possible establishment of future connections, should be preserved, so as to be used in case the primary lightpath fails. We show that, by using the multicost approach for solving the RWA with protection problem, great benefits can be achieved both in terms of the connection blocking rate and in terms of the validity period of the backup lightpath. Moreover the multicost approach, by providing a set of candidate lightpaths for each source destination pair, instead of a single one, offers ease and flexibility in selecting the primary and the backup lightpaths.

This paper evaluates a centralised impairment-aware path restoration approach for GMPLS-controlled transparent optical networks. Experimental results on a 14-node network test-bed show successful QoT compliant path restoration of around 3.6 seconds.

Ever-increasing bandwidth demands and higher flexibility are the main challenges for the next generation optical core networks. A new trend in order to address these challenges is to consider the impairments of the lightpaths during the design of optical networks. In our work, we focus on translucent optical networks, where some lightpaths are routed transparently, whereas others go through a number of regenerators. We present a cost analysis of design strategies, which are based either on an exact Quality of Transmission (QoT) validation or on a relaxed one and attempt to reduce the amount of regenerators used. In the exact design strategy, regenerators are required if the QoT of a candidate lightpath is below a predefined threshold, assuming empty network conditions. In the relaxed strategy, this predefined threshold is lower, while it is assumed that the network is fully loaded. We evaluate techno-economically the suggested design solutions and also show that adding more flexibility to the optical nodes has a large impact to the total infrastructure cost.

In transparent wavelength routed optical networks, the signal quality degrades due to physical layer impairments. Certain physical effects make routing decisions made for one lightpath affect and be affected by the decisions for other lightpaths. To safely establish a lightpath for a new connection two main approaches can be used. The most common approach is to select a lightpath that has acceptable transmission quality under the worst case interference assumption. This ensures that the selected lightpath will not become infeasible due to the possible establishment of future interfering connections, but it sacrifices candidate path space for a quick and stable lightpath selection process. The second approach is to consider the actual current network utilization and account for the interference among lightpaths so as to perform a cross layer optimization between the network and physical layers. In the latter approach, the algorithm has to evaluate and check if the establishment of the new lightpath turns infeasible some of the already established connections. The question that arises is whether the performance benefits obtained through the second approach are worth the added complexity introduced by the cross-layer optimization required.

In this paper we propose an energy-aware broadcast algorithm for wireless networks. Our algorithm is based on the multicost approach and selects the set of nodes that by transmitting implement broadcasting in an optimally energy-efficient way. The energy-related parameters taken into account are the node transmission power and the node residual energy. The algorithm’s complexity however is non-polynomial, and therefore, we propose a relaxation producing a near-optimal solution in polynomial time. We also consider a distributed information exchange scheme that can be coupled with the proposed algorithms and examine the overhead introduced by this integration. Using simulations we show that the proposed algorithms outperform other solutions in the literature in terms of energy efficiency. Moreover, it is shown that the near-optimal algorithm obtains most of the performance benefits of the optimal algorithm at a smaller computational overhead.

In this work we present two mobile, locative and collaborative distributed games that are played using wireless sensor devices. We briefly present the architecture of the two games and demonstrate their capabilities. The key characteristic of these games is that players interact with each other and their surrounding environment by moving, running and gesturing as a means to perform game related actions, using sensor devices. We demonstrate our system's implementation, which uses a combination of JAVA Standard and Mobile editions.

In this work we study the distributed implementation of multicost routing in mobile ad hoc networks. In contrast to single-cost routing, where each path is characterized by a scalar, in multicost routing a vector of cost parameters is assigned to each link, from which the cost vectors of the paths are calculated. These parameters are combined according to an optimization function for selecting the optimal path. Up until now the performance of multicost routing in ad hoc networks has been evaluated either at a theoretical level or by assuming that nodes are static and have full knowledge of the network topology and nodes' state. In the present paper we assess the performance of multicost routing, based on energy-related parameters, in mobile ad hoc networks by embedding its logic in the Dynamic Source Routing (DSR) algorithm, which is a well-known distributed routing algorithm. We compare the performance of the multicost-DSR algorithm to that of the original DSR algorithm under various node mobility scenarios. The results confirm that the multicost-DSR algorithm improves the performance of the network in comparison to the original DSR, by reducing energy consumption overall in the network, spreading energy consumption more uniformly across the network, and reducing the packet drop probability and delivery delay.