903722
Mobile telemedicine sensor networks with low-energy data query and network lifetime considerations
In this paper, we use an integrated architecture that takes advantage of the low cost mobile sensor networks and 3G cellular networks to accommodate multimedia medical calls with differentiated Quality-of-Service (QoS) requirements. We propose a low-energy, distributed, and concentric-zone-based data query mechanism that takes advantages of hierarchical ad hoc routing algorithms to enable a medical specialist to collect physiological data from mobile and/or remote patients. The medical specialist uses cellular network to report patients' data to the medical center. Moreover, we propose a transmission scheme among different zones with balance-based energy efficiency, which can extend network lifetime. We evaluate the validity of our proposals through simulations and analyze their performance. Our results clearly indicate the energy efficiency of the proposed sensor network query algorithms and the efficiency of our multiclass medical call admission control scheme in terms of meeting the multimedia telemedicine QoS requirements.
17279570
Protocol Design and Optimization for Delay/Fault-Tolerant Mobile Sensor Networks
While extensive studies have been carried out in the past several years for many sensor applications, they cannot be applied to the network with extremely low and intermittent connectivity, dubbed the delay/fault-tolerant mobile sensor network (DFT-MSN). Without end-to-end connections due to sparse network density and sensor node mobility, routing in DFT-MSN becomes localized and ties closely to medium access control, which naturally calls for merging Layer 3 and Layer 2 protocols in order to reduce overhead and improve network efficiency. DFT-MSN is fundamentally an opportunistic network, where the communication links exist only with certain probabilities and become the scarcest resource. At the same time, the sensor nodes in DFT-MSN have very limited battery power like those in other sensor networks. Clearly, there is a tradeoff between link utilization and energy efficiency. To address this tradeoff, we develop a cross-layer data delivery protocol for DFT-MSN, which includes two phases, i.e., the asynchronous phase and the synchronous phase. In the first phase, the sender contacts its neighbors to identify a set of appropriate receivers. Since no central control exists, the communication in the first phase is contention-based. In the second phase, the sender gains channel control and multicasts its data message to the receivers. Furthermore, several optimization issues in these two phases are identified, with solutions provided to reduce the collision probability and to balance between link utilization and energy efficiency. Our results show that the proposed cross-layer data delivery protocol for DFT-MSN achieves a high message delivery ratio with low energy consumption and an acceptable delay.
1622745
Replication-based efficient data delivery scheme (red) for delay/fault-tolerant mobile sensor network (DFT-MSN)
The delay/fault-tolerant mobile sensor network (DFT-MSN) has been proposed recently for pervasive information gathering. DFT-MSN distinguishes itself from conventional sensor networks by several unique characteristics such as sensor mobility, loose connectivity, and delay/fault tolerability. The mainstream approaches for sensor networking/communication cannot be applied in DFT-MSN directly. In this paper we propose a replication-based efficient data delivery (RED) scheme based on erasure coding technology tailored for DFT-MSN. RED consists of two key components for data transmission and message management, respectively. The former makes decision on when and where to transmit data messages according to the delivery probability. The latter decides the optimal erasure coding parameters (including the number of data blocks and the needed redundancy) based on its current delivery probability, in order to achieve the desired data delivery ratio while minimizing overhead at the same time. Extensive simulation has been carried out for performance evaluation. Compared with other approaches, the proposed RED data delivery scheme achieves high message delivery ratio with low transmission overhead and data management complexity
17331850
A Systematic Approach to Uncover Security Flaws in GUI Logic
To achieve end-to-end security, traditional machine-to-machine security measures are insufficient if the integrity of the human-computer interface is compromised. GUI logic flaws are a category of software vulnerabilities that result from logic bugs in GUI design/implementation. Visual spoofing attacks that exploit these flaws can lure even security- conscious users to perform unintended actions. The focus of this paper is to formulate the problem of GUI logic flaws and to develop a methodology for uncovering them in software implementations. Specifically, based on an in-depth study of key subsets of Internet Explorer (IE) browser source code, we have developed a formal model for the browser GUI logic and have applied formal reasoning to uncover new spoofing scenarios, including nine for status bar spoofing and four for address bar spoofing. The IE development team has confirmed all these scenarios and has fixed most of them in their latest build. Through this work, we demonstrate that a crucial subset of visual spoofing vulnerabilities originate from GUI logic flaws, which have a well-defined mathematical meaning allowing a systematic analysis.
2061833
A machine learning based approach for table detection on the web
Table is a commonly used presentation scheme, especially for describing relational information. However, table understanding remains an open problem. In this paper, we consider the problem of table detection in web documents. Its potential applications include web mining, knowledge management, and web content summarization and delivery to narrow-bandwidth devices. We describe a machine learning based approach to classify each given table entity as either genuine or non-genuine. Various features reflecting the layout as well as content characteristics of tables are studied.In order to facilitate the training and evaluation of our table classifier, we designed a novel web document table ground truthing protocol and used it to build a large table ground truth database. The database consists of 1,393 HTML files collected from hundreds of different web sites and contains 11,477 leaf TABLE elements, out of which 1,740 are genuine tables. Experiments were conducted using the cross validation method and an F-measure of 95.89% was achieved.
2865514
MARio: mobility-adaptive routing using route lifetime abstractions in mobile ad hoc networks
Mobile Ad hoc NETworks (MANETs) often have fast-changing and unpredictable mobility. This is especially true for recently emerging mobile sensor networks [7] and delay tolerant networks [2], where extreme network conditions are prevalent. To better adjust to such network conditions, we propose to deconstruct the underlying node mobility into a set of abstractions that can be readily leveraged for driving dynamic routing decisions. In particular, we investigate the feasibility of using route lifetime to abstract mobility. Through extensive simulations on DSR, we demonstrate up to 31% improvement in packet delivery rate and 53% improvement in average end-to-end packet latency, using our proposed route prefetch and decay techniques that leverage knowledge of route lifetimes.
1078542
Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet
Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high `data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless and sensor applications.
21557809
Formal description of the cognitive process of problem solving
One of the fundamental human cognitive processes is problem solving. Most of the decisions we make relate to some kind of problems we try to solve no matter how trivial and critical the problem may be. The problem solving process entails performing in a new situation with information acquired and knowledge learned from past situations. As a higher level cognitive process, problem solving involves the correlation process effort to connect newly encounter problem object(s) with the object-attribute-relation (OAR) model representation of knowledge in the brain. The goal of problem solving is to search along various solution paths within the problem solver's knowledge base in the memory. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of problem-solving goals and a set of alternative paths. This paper presents a mathematical and cognitive model that describes problem solving as a cognitive process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is then formally and rigorously described using real-time process algebra (RTPA) base on the aforementioned models. Extended discussions are presented on applications of the cognitive process model of problem solving in software engineering and psychology.