Performance Evaluation of HTTP/2 over TLS+TCP and HTTP/2 over QUIC in a Mobile Network

With the development of technology and the increasing requirement for Internet speed, the web page load time is becoming more and more important in the current society. However, with the increasing scale of data transfer volume, it is hard for the current bandwidth used on the Internet to catch the ideal standard. In OSI protocol stack, the transport layer and application layer provide the ability to determine the package transfer time. The web page load time is determined by the header of the package when the package is launched into the application layer. To improve the performance of the web page by reducing web page load time, HTTP/2 and QUIC has been designed in the industry. We have shown experimentally, that when compared with HTTP/2, QUIC results in lower response time and better network traffic efficiency

Tratamentul melanomului malign: performanţe şi succese

Metodele de tratament al melanomului malign prezintă multe discuţii. Tratamentul chirurgical este aproape unanim recunoscut ca metodă de elecţie. La IOM preoperator folosim metoda criogenică pentru prevenirea infi ltrării elementelor tumorale în timpul intervenţiei chirurgicale. Cu metoda propusă de noi au fost trataţi 121 de pacienţi cu melanom al regiunii capului şi gâtului, stadiile II şi III. Rezultatele tratamentului permit includerea criodestrucţiei ca element important în tratamentul chirurgical al melanomului malign

Stigmergic QoS Optimisation for Flexible Service Composition in Mobile Environments

With the increasing number of resource-rich handsets equipped with diverse wireless communication technologies, users within a limited geographical area can share the services deployed on their mobile devices to form service-sharing communities. By leveraging the computing resources on nearby devices, new service-based applications can be developed to expand users\u27 service options. Many applications from multiple domains have the potential for improvement with flexible, dynamic service composition, including automotive (e.g., real-time hazard warnings), energy demand-side management (e.g., communities maximising use of renewable energy while catering to individual home needs), and FinTech (e.g., fast insurance response). Automatic planning, with adaptive composition recovery mechanisms, has been used to tackle complex service provisioning in such dynamic environments. Existing service composition proposals generate a service dependency graph based on the interoperable relationships between available services, and use goal-driven techniques to discover paths that can functionally satisfy user requests. Apart from functional requirements, though, Quality of Service (QoS) such as execution reliability and latency are also major concerns that impact users\u27 satisfaction. Finding paths in this graph that can functionally satisfy a user\u27s request while simultaneously guaranteeing user-acceptable QoS levels is difficult in mobile environments. Given mobile devices\u27 limited communication ranges, the frequent network topology changes, and services with time-dependent QoS, the existing proposals for QoS-optimal service composition trade-off computational efficiency for optimality to provide only best-effort QoS. The existing mechanisms also use a-priori articulation of the QoS objectives\u27 weights, which does not allow for the exploration of different QoS trade-offs. These relative weights might differ at runtime, and the constant enquiry for user\u27s preferences can inhibit the development of automatic, planning-based service composition. This thesis presents SBOTI (Stigmergic-Based OpTImisation), a decentralised, QoS optimisation mechanism for automatic, planning-based service composition. SBOTI uses a community of homogeneous, mobile software agents, which share the same goal, to effectively and efficiently approximate the set of QoS-optimal service composition configurations available in a geographically-limited, mobile environment. The proposed mechanism uses an iterative, reinforcement-based approach to control the trade-off between computational efficiency and the optimality of the identified service composition solutions. SBOTI incorporates a non-dominated sorting technique to identify the Pareto-optimal set solutions, which allows the user to explore various QoS trade-offs. To control the diversity of the solutions in this set, SBOTI globally updates both dominated and non-dominated solutions using digital pheromones. To allow for exploration of new service composition configurations that may emerge as a result of providers\u27 mobility, SBOTI uses an adaptation procedure that limits the amount of pheromone on previously identified solutions. SBOTI also engages multiple communities, with diverse properties, to collaboratively address the computational efficiency and optimality concerns introduced by a single community of homogeneous agents. SBOTI is evaluated using simulations under various dynamic conditions. The evaluation metrics are the size of the dominated space, which indicates the optimality of the identified set of solutions, and communication overhead. Baselines for comparison are SimDijkstra, GoCoMo and a Random approach. Also, an utility metric is used to compare the performance of SBOTI with the baselines that require a-priori articulation of user preferences. The evaluation results illustrate both the strengths and the limitations of SBOTI in a mobile environment, under different network densities and mobility speeds

2019 IEEE World Congress on Services (SERVICES)

The proliferation of Internet of Things (IoT) and the success of resource-rich cloud services have pushed the data processing horizon towards the edge of the network. This has the potential to address bandwidth costs, and latency, availability and data privacy concerns. Serverless computing, a cloud computing model for stateless and event-driven applications, promises to further improve Quality of Service (QoS) by eliminating the burden of always-on infrastructure through ephemeral containers. Open source serverless frameworks have been introduced to avoid the vendor lock-in and computation restrictions of public cloud platforms and to bring the power of serverless computing to on-premises deployments. In an IoT environment, these frameworks can leverage the computational capabilities of devices in the local network to further improve QoS of applications delivered to the user. However, these frameworks have not been evaluated in a resource-constrained, edge computing environment. In this work we evaluate four open source serverless frameworks, namely, Kubeless, Apache OpenWhisk, OpenFaaS, Knative. Each framework is installed on a bare-metal, single master, Kubernetes cluster. We use the JMeter framework to evaluate the response time, throughput and success rate of functions deployed using these frameworks under different workloads. The evaluation results are presented and open research opportunities are discussed