Exploiting logical mobility in mobile computing middleware

We consider the following forms of mobile interactions: client/server interactions, whereby the request of a client triggers the execution of a unit of code in a server and returns the results to the client; remote evaluation, where a device can send code to another host, have it executed and retrieve the result; code on demand, where a host can request a unit of code from another device to be retrieved and executed; and mobile agents, where an agent is an autonomous unit of code that decides when and where to migrate. Moreover, we consider devices that can be nomadically connected to a fixed network, devices that are constantly connected to a fixed network over a wireless connection, devices that are connected to adhoc networks and any combinations of the above

The SATIN component system - a metamodel for engineering adaptable mobile systems

Mobile computing devices, such as personal digital assistants and mobile phones, are becoming increasingly popular, smaller, and more capable. We argue that mobile systems should be able to adapt to changing requirements and execution environments. Adaptation requires the ability-to reconfigure the deployed code base on a mobile device. Such reconfiguration is considerably simplified if mobile applications are component-oriented rather than monolithic blocks of code. We present the SATIN (system adaptation targeting integrated networks) component metamodel, a lightweight local component metamodel that offers the flexible use of logical mobility primitives to reconfigure the software system by dynamically transferring code. The metamodel is implemented in the SATIN middleware system, a component-based mobile computing middleware that uses the mobility primitives defined in the metamodel to reconfigure both itself and applications that it hosts. We demonstrate the suitability of SATIN in terms of lightweightedness, flexibility, and reusability for the creation of adaptable mobile systems by using it to implement, port, and evaluate a number of existing and new applications, including an active network platform developed for satellite communication at the European space agency. These applications exhibit different aspects of adaptation and demonstrate the flexibility of the approach and the advantages gaine

Q-CAD: QoS and Context Aware Discovery framework for adaptive mobile systems

This paper presents Q-CALl, a resource discovery framework that enables pervasive computing applications to discover and select the resource(s) best satisfying the user needs, taking the current execution context and quality-ofservice (QoS} requirements into account. The available resources are first screened, so that only those suirable to the current execution context of the application will be considered; the shortlisted resources are then evaluated against the QoS needs of the application, and a binding is established to the best available

Adaptive routing for intermittently connected mobile ad hoe networks

The vast majority of mobile ad hoc networking research makes a very large assumption: that communication can only take place between nodes that are simultaneously accessible within in the same connected cloud (i.e., that communication is synchronous). In reality, this assumption is likely to be a poor one, particularly for sparsely or irregularly populated environments.In this paper we present the Context-Aware Routing (CAR) algorithm. CAR is a novel approach to the provision of asynchronous communication in partially-connected mobile ad hoc networks, based on the intelligent placement of messages. We discuss the details of the algorithm, and then present simulation results demonstrating that it is possible for nodes to exploit context information in making local decisions that lead to good delivery ratios and latencies with small overheads.</p

Towards a mobile computing middleware: a synergy of reflection and mobile code techniques

The increasing popularity of wireless devices, such as mobile phones, personal digital assistants, watches and the like. is enabling new classes of applications that present challenging problems to designers. Applications have to be aware of, and adapt to, frequent variations in the context of execution, such as fluctuating network bandwidth, decreasing batten, power, changes in location or device capabilities, and so on. In this paper, we argue that middleware solutions for wired distributed systems cannot be used in a mobile setting, as the principle of transparency that has driven their design runs counter to the new degrees of awareness imposed by mobility: We propose a synergy of reflection and code mobility as a means for middleware to give applications the desired level of flexibility to react to changes happening in the environment, including those that have not necessarily been foreseen by middleware designers. We ruse the sharing and processing of images as an application scenario to highlight the advantages of our approach

Epcast: Controlled Dissemination in Human-based Wireless Networks by means of Epidemic Spreading Models

Epidemics-inspired techniques have received huge attention in recent years from the distributed systems and networking communities. These algorithms and protocols rely on probabilistic message replication and redundancy to ensure reliable communication. Moreover, they have been successfully exploited to support group communication in distributed systems, broadcasting, multicasting and information dissemination in fixed and mobile networks. However, in most of the existing work, the probability of infection is determined heuristically, without relying on any analytical model. This often leads to unnecessarily high transmission overheads. In this paper we show that models of epidemic spreading in complex networks can be applied to the problem of tuning and controlling the dissemination of information in wireless ad hoc networks composed of devices carried by individuals, i.e., human-based networks. The novelty of our idea resides in the evaluation and exploitation of the structure of the underlying human network for the automatic tuning of the dissemination process in order to improve the protocol performance. We evaluate the results using synthetic mobility models and real human contacts traces

TCP over High Speed Variable Capacity Links: A Simulation Study for Bandwidth Allocation

New optical network technologies provide opportunities for fast, controllable bandwidth management. These technologies can now explicitly provide resources to data paths, creating demand driven bandwidth reservation across networks where an applications bandwidth needs can be meet almost exactly. Dynamic synchronous Transfer Mode (DTM) is a gigabit network technology that provides channels with dynamically adjustable capacity. TCP is a reliable end-to-end transport protocol that adapts its rate to the available capacity. Both TCP and the DTM bandwidth can react to changes in the network load, creating a complex system with inter-dependent feedback mechanisms. The contribution of this work is an assessment of a bandwidth allocation scheme for TCP flows on variable capacity technologies. We have created a simulation environment using ns-2 and our results indicate that the allocation of bandwidth maximises TCP throughput for most flows, thus saving valuable capacity when compared to a scheme such as link over-provisioning. We highlight one situation where the allocation scheme might have some deficiencies against the static reservation of resources, and describe its causes. This type of situation warrants further investigation to understand how the algorithm can be modified to achieve performance similar to that of the fixed bandwidth case

Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations

Continuous audio analysis from embedded and mobile devices is an increasingly important application domain. More and more, appliances like the Amazon Echo, along with smartphones and watches, and even research prototypes seek to perform multiple discriminative tasks simultaneously from ambient audio; for example, monitoring background sound classes (e.g., music or conversation), recognizing certain keywords (‘Hey Siri’ or ‘Alexa’), or identifying the user and her emotion from speech. The use of deep learning algorithms typically provides state-of-the-art model performances for such general audio tasks. However, the large computational demands of deep learning models are at odds with the limited processing, energy and memory resources of mobile, embedded and IoT devices. In this paper, we propose and evaluate a novel deep learning modeling and optimization framework that speci cally targets this category of embedded audio sensing tasks. Although the supported tasks are simpler than the task of speech recognition, this framework aims at maintaining accuracies in predictions while minimizing the overall processor resource footprint. The proposed model is grounded in multi-task learning principles to train shared deep layers and exploits, as input layer, only statistical summaries of audio lter banks to further lower computations. We nd that for embedded audio sensing tasks our framework is able to maintain similar accuracies, which are observed in comparable deep architectures that use single-task learning and typically more complex input layers. Most importantly, on an average, this approach provides almost a 2.1⇥ reduction in runtime, energy, and memory for four separate audio sensing tasks, assuming a variety of task combinations.Microsoft Researc

Some Considerations on the Behaviour of Bolted Stainless-Steel Beam-to-Column Connections: A Simplified Analytical Approach

Stainless-steel has proven to be a first-class material with unique mechanical properties for a variety of applications in the building and construction industry. High ductility, strain hardening, durability and aesthetic appeal are only a few of them. From a specific point of view, its nonlinear stress–strain behaviour appears capable of providing a significant increase in the rotational capacity of stainless-steel connections. This, in turn, may provide significant benefits for the overall response of a structure in terms of capacity and ductility. However, the bulk of the research on stainless-steel that has been published so far has mostly ignored the analysis of the deformation capabilities of the stainless-steel connections and has mostly focused on the structural response of individual members, such as beams or columns. For such a reason, the present study aims to contribute to the general understanding of the behaviour of stainless-steel connections from a conceptual, numerical and design standpoint. After a brief review of the available literature, the influence of the use of stainless-steel for column–beam connections is discussed from a theoretical standpoint. As a novel contribution, a different approach to compute the pseudo-plastic moment resistance that takes into account the post-elastic secant stiffness of the stainless-steel is proposed. Successively, a refined finite element model is employed to study the failure of stainless-steel column–beam connections. Finally, a critical assessment of the employment of carbon-steel-based design guidelines for stainless-steel connections provided by the Eurocode 3 design (EN 1993-1-8) is performed. The findings prove the need for the development of novel design approaches and more precise capacity models capable of capturing the actual stainless-steel joint response and their impact on the overall ductility and capacity of the whole structure

Small-world behavior in time-varying graphs

Connections in complex networks are inherently fluctuating over time and exhibit more dimensionality than analysis based on standard static graph measures can capture. Here, we introduce the concepts of temporal paths and distance in time-varying graphs. We define as temporal small world a time-varying graph in which the links are highly clustered in time, yet the nodes are at small average temporal distances. We explore the small-world behavior in synthetic time-varying networks of mobile agents, and in real social and biological time-varying systems.Comment: 5 pages, 2 figure