Packet reordering, high speed networks and transport protocol performance

We performed end-to-end measurements of UDP/IP flows across an Internet backbone network. Using this data, we characterized the packet reordering processes seen in the network. Our results demonstrate the high prevalence of packet reordering relative to packet loss, and show a strong correlation between packet rate and reordering on the network we studied. We conclude that, given the increased parallelism in modern networks and the demands of high performance applications, new application and protocol designs should treat packet reordering on an equal footing to packet loss, and must be robust and resilient to both in order to achieve high performance

Prototyping the recursive internet architecture: the IRATI project approach

In recent years, many new Internet architectures are being proposed to solve shortcomings in the current Internet. A lot of these new architectures merely extend the current TCP/IP architecture and hence do not solve the fundamental cause of these problems. The Recursive Internet Architecture (RINA) is a true new network architecture, developed from scratch, building on lessons learned in the past. RINA prototyping efforts have been ongoing since 2010, but a prototype on which a commercial RINA implementation can be built has not been developed yet. The goal of the IRATI research project is to develop and evaluate such a prototype in Linux/OS. This article focuses on the software design required to implement a network stack in Linux/OS. We motivate the placement of, and communication between, the different software components in either the kernel or user space. The first open source prototype of the IRATI implementation of RINA will be available in June 2014 for researchers, developers, and early adopters

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs

Spacelab system analysis: A study of the Marshall Avionics System Testbed (MAST)

An analysis of the Marshall Avionics Systems Testbed (MAST) communications requirements is presented. The average offered load for typical nodes is estimated. Suitable local area networks are determined

Service quality measurements for IPv6 inter-networks

Measurement-based performance evaluation of network traffic is becoming very important, especially for networks trying to provide differentiated levels of service quality to the different application flows. The non-identical response of flows to the different types of network-imposed performance degradation raises the need for ubiquitous measurement mechanisms, able to measure numerous performance properties, and being equally applicable to different applications and transports. This paper presents a new measurement mechanism, facilitated by the steady introduction of IPv6 in network nodes and hosts, which exploits native features of the protocol to provide support for performance measurements at the network (IP) layer. IPv6 Extension Headers have been used to carry the triggers involving the measurement activity and the measurement data in-line with the payload data itself, providing a high level of probability that the behaviour of the real user traffic flows is observed. End-to-end one-way delay, jitter, loss, and throughput have been measured for applications operating on top of both reliable and unreliable transports, over different-capacity IPv6 network configurations. We conclude that this technique could form the basis for future Internet measurements that can be dynamically deployed where and when required in a multi-service IP environment