Biblio

Over the past decade, distributed CSMA, which forms the basis for WiFi, has been deployed ubiquitously to provide seamless and high-speed mobile internet access. However, distributed CSMA might not be ideal for future IoT/M2M applications, where the density of connected devices/sensors/controllers is expected to be orders of magnitude higher than that in present wireless networks. In such high-density networks, the overhead associated with completely distributed MAC protocols will become a bottleneck. Moreover, IoT communications are likely to have strict QoS requirements, for which the `best-effort' scheduling by present WiFi networks may be unsuitable. This calls for a clean-slate redesign of the wireless MAC taking into account the requirements for future IoT/M2M networks. In this paper, we propose a reservation-based (for minimal overhead) wireless MAC designed specifically with IoT/M2M applications in mind.

The tremendous growth of cloud computing and large-scale data analytics highlight the importance of reducing datacenter power consumption and environmental impact of brown energy. While many Internet service operators have at least partially powered their datacenters by green energy, it is challenging to effectively utilize green energy due to the intermittency of renewable sources, such as solar or wind. We find that the geographical diversity of internet-scale services can be carefully scheduled to improve the efficiency of applying green energy in datacenters. In this paper, we propose a holistic heterogeneity-aware cloud workload management approach, sCloud, that aims to maximize the system goodput in distributed self-sustainable datacenters. sCloud adaptively places the transactional workload to distributed datacenters, allocates the available resource to heterogeneous workloads in each datacenter, and migrates batch jobs across datacenters, while taking into account the green power availability and QoS requirements. We formulate the transactional workload placement as a constrained optimization problem that can be solved by nonlinear programming. Then, we propose a batch job migration algorithm to further improve the system goodput when the green power supply varies widely at different locations. Finally, we extend sCloud by integrating a flexible batch job manager to dynamically control the job execution progress without violating the deadlines. We have implemented sCloud in a university cloud testbed with real-world weather conditions and workload traces. Experimental results demonstrate sCloud can achieve near-to-optimal system performance while being resilient to dynamic power availability. sCloud with the flexible batch job management approach outperforms a heterogeneity-oblivious approach by 37 percent in improving system goodput and 33 percent in reducing QoS violations.

IEC61850 and IEC62351 combined provide a set of security promises for the communications channels that are used to run a substation automation system (SAS), that use IEC61850 based technologies. However, one area that is largely untouched by these security promises is the generic object oriented substation events (GOOSE) messaging service. GOOSE is designed to multicast commands and data across a substation within hard real time quality of service (QoS) requirements. This means that GOOSE is unable to implement the required security technologies as the added latency to any message would violate the QoS.

In the last years, networking scenarios have been evolving, hand-in-hand with new and varied applications with heterogeneous Quality of Service (QoS) requirements. These requirements must be efficiently and effectively delivered. Given its static layered structure and almost complete lack of built-in QoS support, the current TCP/IP-based Internet hinders such an evolution. In contrast, the clean-slate Recursive InterNetwork Architecture (RINA) proposes a new recursive and programmable networking model capable of evolving with the network requirements, solving in this way most, if not all, TCP/IP protocol stack limitations. Network providers can better deliver communication services across their networks by taking advantage of the RINA architecture and its support for QoS. This support allows providing complete information of the QoS needs of the supported traffic flows, and thus, fulfilment of these needs becomes possible. In this work, we focus on the importance of path selection to better ensure QoS guarantees in long-haul RINA networks. We propose and evaluate a programmable strategy for path selection based on flow QoS parameters, such as the maximum allowed latency and packet losses, comparing its performance against simple shortest-path, fastest-path and connection-oriented solutions.

A cyber-attack detection system issues alerts when an attacker attempts to coerce a trusted software application to perform unsafe actions on the attacker's behalf. One way of issuing such alerts is to create an application-agnostic cyber- attack detection system that responds to prevalent software vulnerabilities. The creation of such an autonomic alert system, however, is impeded by the disparity between implementation language, function, quality-of-service (QoS) requirements, and architectural patterns present in applications, all of which contribute to the rapidly changing threat landscape presented by modern heterogeneous software systems. This paper evaluates the feasibility of creating an autonomic cyber-attack detection system and applying it to several exemplar web-based applications using program transformation and machine learning techniques. Specifically, we examine whether it is possible to detect cyber-attacks (1) online, i.e., as they occur using lightweight structures derived from a call graph and (2) offline, i.e., using machine learning techniques trained with features extracted from a trace of application execution. In both cases, we first characterize normal application behavior using supervised training with the test suites created for an application as part of the software development process. We then intentionally perturb our test applications so they are vulnerable to common attack vectors and then evaluate the effectiveness of various feature extraction and learning strategies on the perturbed applications. Our results show that both lightweight on-line models based on control flow of execution path and application specific off-line models can successfully and efficiently detect in-process cyber-attacks against web applications.

Web Service (WS) plays an important role in today's word to provide effective services for humans and these web services are built with the standard of SOAP, WSDL & UDDI. This technology enables various service providers to register and service sender their intelligent agent based privacy preserving modelservices to utilize the service over the internet through pre established networks. Also accessing these services need to be secured and protected from various types of attacks in the network environment. Exchanging data between two applications on a secure channel is a challenging issue in today communication world. Traditional security mechanism such as secured socket layer (SSL), Transport Layer Security (TLS) and Internet Protocol Security (IP Sec) is able to resolve this problem partially, hence this research paper proposes the privacy preserving named as HTTPI to secure the communication more efficiently. This HTTPI protocol satisfies the QoS requirements, such as authentication, authorization, integrity and confidentiality in various levels of the OSI layers. This work also ensures the QoS that covers non functional characteristics like performance (throughput), response time, security, reliability and capacity. This proposed intelligent agent based model results in excellent throughput, good response time and increases the QoS requirements.
 

Wireless mesh networks (WMNs) are attracting more and more real time applications. This kind of applications is constrained in terms of Quality of Service (QoS). Existing works in this area are mostly designed for mobile ad hoc networks, which, unlike WMNs, are mainly sensitive to energy and mobility. However, WMNs have their specific characteristics (e.g. static routers and heavy traffic load), which require dedicated QoS protocols. This paper proposes a novel traffic regulation scheme for multimedia support in WMNs. The proposed scheme aims to regulate the traffic sending rate according to the network state, based on the buffer evolution at mesh routers and on the priority of each traffic type. By monitoring the buffer evolution at mesh routers, our scheme is able to predict possible congestion, or QoS violation, early enough before their occurrence; each flow is then regulated according to its priority and to its QoS requirements. The idea behind the proposed scheme is to maintain lightly loaded buffers in order to minimize the queuing delays, as well as, to avoid congestion. Moreover, the regulation process is made smoothly in order to ensure the continuity of real time and interactive services. We use the interval type-2 fuzzy logic system (IT2 FLS), known by its adequacy to uncertain environments, to make suitable regulation decisions. The performance of our scheme is proved through extensive simulations in different network and traffic load scales.