Min Xi

Does wireless sensor network scale? A measurement study on GreenOrbs

Sensor networks are deemed suitable for large-scale deployments in the wild for a variety of applications. In spite of the remarkable efforts the community put to build the sensor systems, an essential question still remains unclear at the system level, motivating us to explore the answer from a point of real-world deployment view. Does the wireless sensor network really scale? We present findings from a large-scale operating sensor network system, GreenOrbs, with up to 330 nodes deployed in the forest. We instrument such an operating network throughout the protocol stack and present observations across layers in the network. Based on our findings from the system measurement, we propose and make initial efforts to validate three conjectures that give potential guidelines for future designs of large-scale sensor networks. 1) A small portion of nodes bottlenecks the entire network, and most of the existing network indicators may not accurately capture them. 2) The network dynamics mainly come from the inherent concurrency of network operations instead of environment changes. 3) The environment, although the dynamics are not as significant as we assumed, has an unpredictable impact on the sensor network. We suggest that an event-based routing structure can be trained and thus better adapted to the wild environment when building a large-scale sensor network.

Run to Potential: Sweep Coverage in Wireless Sensor Networks

Wireless sensor networks have become a promising technology in monitoring physical world. In many applications with wireless sensor networks, it is essential to understand how well an interested area is monitored (covered) by sensors. The traditional way of evaluating sensor coverage requires that every point in the field should be monitored and the sensor network should be connected to transmit messages to a processing center (sink). Such a requirement is too strong to be financially practical in many scenarios. In this study, we address another type of coverage problem, sweep coverage, when we utilize mobile nodes as supplementary in a sparse and probably disconnected sensor network. Different from previous coverage problem, we focus on retrieving data from dynamic Points of Interest (POIs), where a sensor network does not necessarily have fixed data rendezvous points as POIs. Instead, any sensor node within the network could become a POI. We first analyze the relationship among information access delay, information access probability, and the number of required mobile nodes. We then design a distributed algorithm based on a virtual 3D map of local gradient information to guide the movement of mobile nodes to achieve sweep coverage on dynamic POIs. Using the analytical results as the guideline for setting the system parameters, we examine the performance of our algorithm compared with existing approaches.

An offset algorithm for conflict resolution in context-aware computing

In context-aware system, applications should adjust their execution policies in the light of context information of equipment, such as equipments position, electric power, network bandwidth, and so on. In various context-aware systems, an important solution is to isolate executable codes in different context into a number of program segments and to select different execution policies according to the context in the process of operation, thus increasing the programming flexibility. Since not all possible contexts can be taken into consideration in the definition of policies, several policies might meet the current context simultaneously in some given environments, thus resulting in policy conflict. This paper proposes a kind of conflict solution algorithm, which, through defining the context center of each execution policy, computes the offset between the current context and the center and selects the one closest to the current context as the execution policy in the case of conflict. Experiments testify that the algorithm can effectively eliminate conflicts of policy selection and well manifest the intention of policy definition, making policy selection more reasonable.

A Conflict Resolution Method in Context-Aware Computing

The creation of various mobile devices speeded up the development of context-aware computing. Context-aware applications are able to adjust execution policies at any moment according to context information such as equipments position, electric power, network bandwidth, and so on. In various context-aware systems, an important solution is to isolate executable codes in different context into a number of program segments and to select different execution policies according to the context in the process of operation, thus increasing the programming flexibility. However, the method can result in conflicts, making the system unable to select correct execution policy. This paper proposes a kind of algorithm designed to resolve conflicts. The algorithm calculates the selection center of each policy and the offset value of each conflicting policy under the current context environment. The algorithm will select execution policies through comparing offsets of policies, thus eliminating conflicts. To avoid the problem of policy thrashing resulting from frequent changes of context environment within a small scope, the algorithm modifies the calculate method of offset through the introduction of persistence coefficient. Experiments testify that the algorithm can effectively eliminate conflicts and well manifest the intention of policy definition, making policy selection more reasonable. Meanwhile the algorithm can avoid the thrashing of policy selection, providing more satisfaction to user.

Cache Predicting Algorithm Based on Context-Aware in Pervasive Computing

In pervasive computing, mobile device needs to make data access continuously, but in the influence of network and other factors, it could be disconnected. In order to support the continuous data access in case of disconnection, it needs to predict the possible access of data made by users and cache these data on the mobile client. Through data cache, it could store the data that the user could access in future on the client in advance, therefore the effects of disconnected mobile device on data access could be avoided and the quality of service could be accordingly raised. Among the present buffer management algorithms, the computing process either takes no account of context, or divides the data in groups to make a forecast separately according to the context information. These two methods could not fully consider the trend of the whole user access and the impact of user context on the predicted consequences. This paper puts forward a buffer management algorithm, which establishes the association between various data on the basis of data access records and makes data group; after computing the accessing frequency of data sets over the current contexts, it makes cache replacement of the results in terms of cache residence time and accessing frequency. The results of simulation tests show that this kind of algorithm could effectively improve the cache hit rate in the case of disconnected operation for handheld mobile devices, and better support the disconnected operation of mobile devices.

Allotropy Programming Paradigm for Ubiquitous Computing Environment

Object-oriented method, agent- oriented programming method, aspect-oriented of programming method, formal specification languages, component-based software designing method,.... This incomplete list of methods proposed to solve a conventional well-known problem: how to enhance a software of flexibility and ubiquitous ability. Programming methods have been the crucial task during the past decades, and the results still have not been successful yet. Constructing a suitable programming model for ubiquitous computing based on the pervasive spaces is pedestal in improving the flexibility and adaptability, enhancing the robusticity of ubiquitous systems, and creating an open platform for interoperability, complexity and multiplicity. There are many programming models have been proposed and studied for their feasibilities as the groundwork for implementing in the ubiquitous spaces. We contrast their advantages and disadvantages.

Energy Efficient Multi-rate Based Time Slot Pre-schedule Scheme in WSNs for Ubiquitous Environment

Nowadays, smart spaces occupy an essential part of ubiquitous computing environment. The spaces integrated with wireless sensors networks, actuators and context-aware services become part of our daily life. Smart spaces are equipped with a large number of wireless sensors that aim to collect large quantities of context information, during the process, there exists a large amount of collisions and energy consumption. Therefore, this paper provides a novel multi-rate based local framing pre-schedule scheme to further reduce collisions and improve energy efficiency in CSMA/TDMA hybrid MAC layer of wireless sensor network. This MAC combines CSMA and TDMA functionalities together while obviates their shortcomings. Having been assigned, slot 0 is preserved as the pre-schedule slot, to inform neighbor nodes the schedule of the senders. During the pre-schedule slot, each node knows exactly the schedule of other neighbor nodes. Multi-rate and power scaling are applied to achieve further energy saving by adpoting an acceptable rate rather than maximum rate. Data rate is dynamically adjusted according to the traffic load of sending nodes, in an energy efficient data rate, to save energy. Being compared with Z-MAC in terms of performances, local framing pre-schedule and multi-rate in this experiment achieved further energy efficiency.