Earticle

The smart home concept brings innovation and convenience to our every day's life style. Without context awareness, smart home applications can neither offer adaptive services based on users’ dynamic situations nor provide preferential treatments according to users’ various preferences. Such a design paradigm forces human to live in the world of machines rather than a human-centric world. The use of SIP-protocol allows smart home devices and services to be connected compatibly and effectively. In this paper, we propose an adaptive SIP Context Aware Gateway (SIP-CAG) for the ubiquitous SIP-based services. With the SIPCAG solution, the home owner is able to use preferred devices for communication and to post his/her context information to home appliances or to people and civil society communities on an “as needed” basis.

Pervasive computing calls for new ways of thinking about software and new ways of applying software development techniques. In pervasive computing environments, users will need to interact with collections of devices surrounding them (such as the “system” of smart devices in a user’s home), which we metaphorically term device ecologies. A user can interact with these devices with embedded software and hardware, either directly via the device’s own interface, or automated through scripts executed by a central coordinator. For the latter, we employ a workflow abstraction for the collective operation of devices, which we call decoflow. While executable formal models are typically used at specification time, we maintain and use such models, calling them mirror models, to record the on-going states of devices, their relationships, and the effects that such devices have on the environment. Users effectively update a mirror model of the devices s/he interacts with. The model can be used to predict the effects of decoflows just before execution. Generalizing from mirror models for device ecologies, we propose the novel paradigm of continually updated mirror models for on-going tracking and reasoning about pervasive computing systems which cohabitates with the user.

With the great progress of technologies, computers are embedded into everywhere to make our daily life convenient, efficient and comfortable. Further more, most of them are small, powerful, intelligent and invisible. In a ubiquitous computing environment, support methods for learning are more effective than some traditional ways, such as WBT (Web-Based Training) and e-learning. In this paper, we proposed a support method which aims to encourage a learner to acquire his/her learning habit based on Behavior Analysis. The supports to the learner are provided through a scheduler system, a Ubiquitous Learning Scheduler (ULS). In our design, the learner’s situations are collected by sensors and analyzed by comparing them to his/her learning histories. Based on this information, supports are provided to the learner in order to help him/her forming a good learning style. Our Research results revealed that ULS not only benefited learners to acquire their learning habits but also improved their self-directed learning styles.

Wireless Local Area Networks (WLANs) are becoming a popular way of networking computer equipments in the home and office. In order to support differentiated Quality-of- Service (QoS) in WLANs, the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol allocates multiple Access Categories (ACs) with different priorities, inter-frame spaces, and contention window sizes. This paper presents an improved Medium Access Control (MAC) scheme to enhance the QoS of WLANs based on the idea of using the different increasing functions for each AC to enlarge the size of contention window in the case of transmission collision. The performance of this improved scheme under multimedia applications is extensively investigated and compared with the original EDCA using the wellknown network simulator NS-2. The results show that this scheme is able to achieve higher throughput and medium utilization as well as lower access delay and packet loss probability than the original EDCA. Moreover, it provides a good prioritization level between multiple ACs.

P2P based live streaming applications are growing up rapidly. However, when extending them to WLANs, the bandwidth bottleneck and the high rate of packet loss are usually the major stumbling blocks. To overcome this issue, a new wireless multicast agent mechanism (WiMA) based on the IP multicast scheme for buffer management and scheduling is proposed. First of all, a wireless agent selection method is presented to choose an appropriate agent for WiMA. Then this agent gains media data by interacting with wired neighbor peers as a common P2P node, and transmits these data to other wireless peers in the WLAN by means of multicast pushing and multicast patching. A normal wireless peer requests data according to the strategy of "emergent ones first". Experimental results show that the approach proposed can significantly save bandwidth in WLANs with acceptable start delay and satisfied playing continuity.

Domotic Robotic Cleaners are autonomous devices that are designed to operate almost entirely unattended. In this paper we propose a system that aims to evaluate the performance of such devices by analysis of their trails. This concept of trails is central to our approach, and it encompasses the traditional notion of a path followed by a robot between arbitrary numbers of points in a physical space. We enrich trails with context-specific metadata, such as proximity to landmarks, frequency of visitation, duration, etc. We then process the trail data collected by the robots, we store it an appropriate data structure and derive useful statistical information from the raw data. The usefulness of the derived information is twofold: it can primarily be used to audit the performance of the robotic cleaner –for example, to give an accurate indication of how well a space is covered (cleaned). And secondarily information can be analyzed in real-time to affect the behavior of specific robots – for example to notify a robot that specific areas have not been adequately covered. Towards our first goal, we have developed and evaluated a prototype of our system that uses a particular commercially available robotic cleaner. Our implementation deploys adhoc wireless local networking capability available through a surrogate device mounted onto this commodity robot; the device senses relative proximity to a grid of RFID tags attached to the floor. We report on the performance of this system in experiments conducted in a laboratory environment, which highlight the advantages and limitations of our approach.