High-performance IO demands low-overhead communication between user- and kernel space. This demand can no longer be fulfilled by traditional system calls. Linux's extended Berkeley Packet Filter (BPF) avoids user-/kernel transitions by just-in-time compiling user-provided bytecode and executing it in kernel mode with near-native speed. To still isolate BPF programs from the kernel, they are statically analyzed for memory- and type-safety, which imposes some restrictions but allows for good expressiveness and high performance. However, to mitigate the Spectre vulnerabilities disclosed in 2018, defenses which reject potentially-dangerous programs had to be deployed. We find that this affects 31 % to 54 % of programs in a dataset with 844 real-world BPF programs from popular open-source projects. To solve this, users are forced to disable the defenses to continue using the programs, which puts the entire system at risk.

Operating systems are crucial for the performance of the overall system. Any inefficiency leads to a suboptimal use of the available resources and causes performance loss. The wide range of processors in use today makes it challenging to generate the most efficient code for the current hardware ahead of time. Just-in-time compilation, on the other hand, is able to generate efficient code tailored to the current execution context going beyond the processor, also including operating-system configuration or application demands. Moreover, its configuration can even be adapted at runtime to match the current external and internal requirements. Unfortunately, on-demand compilation of operating-system code has not found widespread use due to inherent difficulties stemming from the fact that any just-in-time approach requires extensive runtime support (e.g., for memory allocation for the generated code) usually provided by the operating system itself. A chicken-and-egg problem is found.

Experimental platforms (testbeds) play a significant role in the evaluation of new and existing technologies. Their popularity has been raised lately as more and more researchers prefer experimentation over simulation as a way for acquiring more accurate results. This imposes significant challenges in testbed operators since an efficient mechanism is needed to manage the testbed's resources and provision them according to the users' needs. In this paper we describe such a framework which was implemented for the management of networking testbeds. We present the design requirements and the implementation details, along with the challenges we encountered during its operation in the NITOS testbed. Significant results were extracted through the experiences of the every day operation of the testbed's management.

While most existing video summarization approaches aim to identify important frames of a video from either a global or local perspective, we propose a top-down approach consisting of scene identification and scene summarization. For scene identification, we represent each frame with global features and utilize a scalable clustering method. We then formulate scene summarization as choosing those frames that best cover a set of local descriptors with minimal redundancy. In addition, we develop a visual word-based approach to make our approach more computationally scalable. Experimental results on two benchmark datasets demonstrate that our proposed approach clearly outperforms the state-of-the-art.

This paper presents a case for the adoption of an information-centric architecture for a global disaster management system. Drawing from a case study of the 2010/2011 Queensland floods, we describe the challenges in providing every participant with relevant and actionable information. We use various examples to argue for a more flexible information dissemination framework which is designed from the ground up to minimise the effort needed to fix the unexpected and unavoidable information acquisition, quality, and dissemination challenges posed by any real disaster.

In this paper, we introduce the Moana network infrastructure. It draws on well-adopted practices from the database and software engineering communities to provide a robust and expressive information-sharing service using hypergraph-based network indirection. Our proposal is twofold. First, we argue for the need for additional layers of indirection used in modern information systems to bring the network layer abstraction closer to the developer's world, allowing for expressiveness and flexibility in the creation of future services. Second, we present a modular and extensible design of the network fabric to support incremental architectural evolution and innovation, as well as its initial evaluation.

The problem of further improving the accuracy of GPS-provided coordinates of vehicles within the same VANET (Vehicular Ad-Hoc Network) is addressed. VANETs can be used to increase the accuracy of each vehicle's computed location by allowing vehicles to share information wth each other. This paper looks at improving the coordinates provided by the GPS devices, given that erroneous measurements are present in the system. The algorithm VLOCI2 is an extension of the VLOCI algorithm by providing location improvement on multi-laned roads. VLOCI2 is shown to perform efficiently when erroneous distance measurements are present in the environment/computations.

We present our work towards building a novel distributed n-tuple store by extending the Kademlia DHT [1] algorithm to support n dimensional keys as well as an multi get operator, where some of the dimensions of the "query" key can be left unspecified.

Multi-interfaced mobile devices can connect to heterogeneous wireless access networks with different capabilities and constraints. Additionally, many bandwidth intensive applications have rather relaxed real time constraints allowing for alternative scheduling mechanisms which can take into account user preferences, network characteristics as well as future network resource availability to better exploit network heterogeneity. The current approaches either simply react to changes, or assume that availability predictions are perfect. In this paper, we propose a scheduling scheme based on stochastic modeling to account for prediction errors. The scheme optimizes overall user utility gain considering imperfect predictions taken over realistic time intervals while catering for different applications' needs. We use 60 days of real user data of many users to demonstrate that it consistently out-performs other non-stochastic and greedy approaches in typical networking environments.

Near-duplicate video shots provide critical visual link between videos and detecting such video shots efficiently and effectively is of paramount importance in many applications such as detecting copyright infringement. In this paper, we propose an improved near-duplicate video shot detection approach by adaptively selecting reference frames for more effective shot representation. The correlation between adjacent frames is measured with Pearson's Correlation Coefficient (PCC) so that a set of compact yet representative reference frames can be selected adaptively in terms of content variation within video shots. Interest points are further extracted from the selected frames to effectively represent shot contents for similarity matching. Comprehensive experimental results on TRECVID-2008 corpus demonstrate that our proposed approach outperforms the state-of-the-art method effectively.

Semantic web is gaining popularity as the candidate for next generation World Wide Web. Distribution of the data across number of physical information stores and proliferation of semantic web data brings variety of non-trivial challenges. One of such challenge is to identify information stores for a given query. This paper presents a framework to address this problem probabilistically and by exchanging the summaries of actual contents. Experimental evaluation shows promising results with high recall for probabilistic approach and lower response time for pre-processed summary exchanges.

Data and service delivery have been historically based on a ''network centric'' model, with datacentres being the focal sources. The amount of energy consumed by these datacentres has become an emerging issue for the companies operating them. Thus, many contributions have proposed solutions to improve the energy efficiency of current datacentre architecture and deployments. A recently proposed approach argues for removing the datacentres from the delivery architecture. Their functionalities will instead be distributed at the edge of the network, directly within operator-managed home devices, such as Home Gateways, or Set-Top-Box (STB). This paper presents a study of the overall energy consumption required by such a community of STBs in order to provide the same services as datacentres. This paper also investigates a possible distributed algorithm to further reduce this overall energy consumption. This algorithm will be deployed over a managed peer-to-peer network of STBs. It will make optimized decisions and instruct unused STBs to switch Off to save energy without altering the general Service Level Agreement. We demonstrate the potential benefit of such an algorithm through an off-line scheduling. Finally, we propose a service-delivery model that allows us to integrate the service availability in the energy optimization problem. The combination of these two models is the first step in the development of our energy optimisation distributed algorithm.

Efficient Information retrieval is the key goal of semantic web. This technology ameliorates the documents with meta-data in a machine readable markup. Well known semantic search engines such as swoogle1or SHOE2use pre-fetched static indexing for efficiently retrieving the requested runtime documents. This paper presents a novel application dependent approach for improving the efficiency and retrieving the content documents based on an ASK type of SPARQL query in a distributed environment. We developed an initial prototype of the system and the performance curve for this approach is discussed in this paper. Observation on the results clearly shows that our approach receives favourable preliminary results.

Modern mobile devices are increasingly capable of simultaneously connecting to multiple access networks with different characteristics. Restricted coverage combined with user mobility will vary the availability of networks for a mobile device. Most proposed solutions for such an environment are reactive in nature, such as performing a vertical handover to the network that offers the highest bandwidth. But the cost of the handover may not be justified if that network is only available for a short time. Knowledge of future network availability and their capabilities are the basis for proactive schemes which will improve network selection and utilization. We have previously proposed a prediction model that can use any available context such as GSM Location Area, WLAN presence or even whether the power cable is plugged in, to predict network availability.

Most mobile devices nowadays can simultaneously connect to different access networks with different characteristics at different times. Most solutions proposed for such an environment are reactive in nature. For example, when networks are encountered, the device performs a vertical handover to the n

Wireless mesh networks (WMN) have attracted considerable interest in years as a convenient, flexible and low-cost alternative to wired communication infrastructures in many contexts. However, the great majority of research on metropolitan-scale WMN has been centered around maximization of available bandwidth, suitable for non-real-time applications such as Internet access for the general public. On the other hand, the suitability of WMN for mission-critical infrastructure applications remains by and large unknown, as protocols typically employed in WMN are, for the most part, not designed for real-time communications. In this paper, we describe the smart transport and roads communications (STaRComm) project at National ICT Australia (NICTA), which sets a goal of designing a wireless mesh network architecture to solve the communication needs of the traffic control system in Sydney, Australia. This system, known as SCATS (Sydney coordinated adaptive traffic system) and used in over 100 cities around the world, connects a hierarchy of several thousand devices - from individual traffic light controllers to regional computers and the central traffic management centre (TMC) - and places stringent requirements on the reliability and latency of the data exchanges. We discuss our experience in the deployment of an initial testbed consisting of 7 mesh nodes placed at intersections with traffic lights, and share the results and insights learned from our measurements and initial trials in the process.

This paper presents an overview of the ORBIT (open access research testbed for next-generation wireless networks) radio grid testbed, that is currently being developed for scalable and reproducible evaluation of next-generation wireless network protocols. The ORBIT testbed consists of an indoor radio grid emulator for controlled experimentation and an outdoor field trial network for end-user evaluations in real-world settings. The radio grid system architecture is described in further detail, including an identification of key hardware and software components. Software design considerations are discussed for the open-access radio node, and for the system-level controller that handles management and control. The process of specifying and running experiments on the ORBIT testbed is explained using simple examples. Experimental scripts and sample results are also provided.

The paper proposes an overlay network architecture for future content delivery services over the Internet. The proposed network is based on a dynamic semantic multicast model where overlay routers forward packets on one or more ports based on hierarchical content descriptors instead of an IP address. Information providers "publish" their content by sending out packets with XML schema-based content headers, and end-users subscribe to the network with an XML "interest-profile". The paper describes the protocol design, discusses its scaling properties, and reports on the performance of the implemented system.

Faster processors are quickly enabling a new class of computationally intensive applications that actively transform information flows. Performing such computation at the terminal end is contrary to current trends toward low-power terminal devices. Moreover, scalability and efficiency concerns are also encouraging service providers to outsource computation when operating under loaded conditions. To address the problem of deploying such applications, we introduce the JOURNEY network model, which provides computation as an integrated network service. Contrary to other distributed computing models, JOURNEY does not attempt to guarantee that a given computational job will indeed be completed. Instead, the JOURNEY model trades off such hard guarantees in favor of architectural simplicity, and hence scalability. In order for the JOURNEY model to be applicable to real-time multimedia flows, we introduce the notion of soft quality-of-service (QoS) that provides a probabilistic bound on the unprocessed packet rate (UPR). Based on this notion, we describe a packet-processing admission control algorithm that additionally takes into consideration a flow's real-time constraints. We also propose a computing router architecture that is based on cluster technology. This architecture can track technology advances in both routing and computing independently. We further present a motivating multimedia application that employs a semantically driven video transcoding service within the JOURNEY framework we implemented, and describe our experience along with performance measurements.

A dynamic framework for quality-of-service (QoS) control of video in distributed multimedia applications is presented The framework allows flexible and efficient video delivery with application-level QoS support. Key components of the framework are: client QoS renegotiation, server source rate control and dynamic bandwidth allocation. The soft-QoS requirements of the application are communicated among the framework components using distributed software objects, called service contracts. A proof-of-concept prototype of a video browser with user-level control of soft-QoS is implemented within the proposed framework. Experiences with the prototype and its performance are discussed. Results suggest that the framework is particularly suitable for the mobile multimedia scenario allowing mobile applications to maintain soft-QoS while roaming without compromising network utilization.

In distributed object systems, remote method invocation attempts to abstract communication between different machines to the level of object method invocation. Link failure in such systems often appears as a failed method invocation, which must be explicitly handled outside the remote object infrastructure. This usually implies that techniques to handle the effects of link failure are embedded within application functionality. The resulting application can become unnecessarily specialized to a particular environment, restricting the situations where it could be used. We explore the possibility of cleanly decoupling policies for handling a link failure from the application. With this goal in mind, we present extensions to the Java RMI system in the context of a distributed system with mobile hosts. An intermittent communication link is typical in such systems, and applications use techniques such as data caching or queuing of method calls to alleviate the effects. We show how such techniques and policies can be implemented generically so that not only does the application become oblivious of them, but also policies can be chosen dynamically depending on a particular situation.

This paper accompanies a demonstration of a variable bit-rate (VBR) video server with scalable quality-of-service (QoS) control. Multimedia applications dynamically demand different QoS grades from servers and networks during a session. Since video is a critical component of distributed multimedia applications, video servers have to be responsive to the applications' requirements and to the availability of resources on heterogeneous terminals and networks. For this purpose a video server has to dynamically scale the source's quality in the control space formed by frame resolution, quantization and display rate. Experiences with a proof-of-concept implementation of a server with scalable QoS control show that it is able to jointly match the target quality of applications, the processing limitations of terminals and the capacity limitations of networks.