2709125
A two-tier data dissemination model for large-scale wireless sensor networks
Sink mobility brings new challenges to large-scale sensor networking. It suggests that information about each mobile sink's location be continuously propagated through the sensor field to keep all sensor nodes updated with the direction of forwarding future data reports. Unfortunately frequent location updates from multiple sinks can lead to both excessive drain of sensors' limited battery power supply and increased collisions in wireless transmissions. In this paper we describe TTDD, a Two-Tier Data Dissemination approach that provides scalable and efficient data delivery to multiple mobile sinks. Each data source in TTDD proactively builds a grid structure which enables mobile sinks to continuously receive data on the move by flooding queries within a local cell only. TTDD's design exploits the fact that sensor nodes are stationary and location-aware to construct and maintain the grid structures with low overhead. We have evaluated TTDD performance through both analysis and extensive simulation experiments. Our results show that TTDD handles multiple mobile sinks efficiently with performance comparable with that of stationary sinks.
23906830
PEAS: a robust energy conserving protocol for long-lived sensor networks
Small, inexpensive sensors with limited memory, computing power and short battery lifetimes are turning into reality. Due to adverse conditions such as high noise levels, extreme humidity or temperatures, or even destructions from unfriendly entities, sensor node failures may become norms rather than exceptions in real environments. To be practical, sensor networks must last for much longer times than that of individual nodes, and have yet to be robust against potentially frequent node failures. This paper presents the design of PEAS, a simple protocol that can build a long-lived sensor network and maintain robust operations using large quantities of economical, short-lived sensor nodes. PEAS extends system functioning time by keeping only a necessary set of sensors working and putting the rest into sleep mode. Sleeping ones wake up now and then, probing the local environment and replacing failed ones. The sleeping periods are self-adjusted dynamically, so as to keep the sensors' wakeup rate roughly constant, thus adapting to high node densities.
8338982
Self-coordinating localized fair queueing in wireless ad hoc networks
Distributed fair queueing in a multihop, wireless ad hoc network is challenging for several reasons. First, the wireless channel is shared among multiple contending nodes in a spatial locality. Location-dependent channel contention complicates the fairness notion. Second, the sender of a flow does not have explicit information regarding the contending flows originated from other nodes. Fair queueing over ad hoc networks is a distributed scheduling problem by nature. Finally, the wireless channel capacity is a scarce resource. Spatial channel reuse, i.e., simultaneous transmissions of flows that do not interfere with each other, should be encouraged whenever possible. In this paper, we reexamine the fairness notion in an ad hoc network using a graph-theoretic formulation and extract the fairness requirements that an ad hoc fair queueing algorithm should possess. To meet these requirements, we propose maximize-local-minimum fair queueing (MLM-FQ), a novel distributed packet scheduling algorithm where local schedulers self-coordinate their scheduling decisions and collectively achieve fair bandwidth sharing. We then propose enhanced MLM-FQ (EMLM-FQ) to further improve the spatial channel reuse and limit the impact of inaccurate scheduling information resulted from collisions. EMLM-FQ achieves statistical short-term throughput and delay bounds over the shared wireless channel. Analysis and extensive simulations confirm the effectiveness and efficiency of our self-coordinating localized design in providing global fair channel access in wireless ad hoc networks.
1236934
A Packet Scheduling Approach to QoS Support in Multihop Wireless Networks
Providing packet-level quality of service (QoS) is critical to support both rate-sensitive and delay-sensitive applications in bandwidth-constrained, shared-channel, multihop wireless networks. Packet scheduling has been a very popular paradigm to ensure minimum throughput and bounded delay access for packet flows. This work describes a packet scheduling approach to QoS provisioning in multihop wireless networks. Besides minimum throughput and delay bounds for each flow, our scheduling disciplines seek to achieve fair and maximum allocation of the shared wireless channel bandwidth. However, these two criteria can potentially be in conflict in a generic-topology multihop wireless network where a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth is possible. In this paper, we propose a new scheduling model that addresses this conflict. The main results of this paper are the following: (a) a two-tier service model that provides a minimum “fair” allocation of the channel bandwidth for each packet flow and additionally maximizes spatial reuse of bandwidth, (b) an ideal centralized packet scheduling algorithm that realizes the above service model, and (c) a practical distributed backoff-based channel contention mechanism that approximates the ideal service within the framework of the CSMA/CA protocol.
1919911
Robust rate adaptation for 802.11 wireless networks
Rate adaptation is a mechanism unspecified by the 802.11 standards, yet critical to the system performance by exploiting the multi-rate capability at the physical layer.I n this paper, we conduct a systematic and experimental study on rate adaptation over 802.11 wireless networks. Our main contributions are two-fold. First, we critique five design guidelines adopted by most existing algorithms. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incur significant performance penalty in certain scenarios. The fundamental challenge is that rate adaptation must accurately estimate the channel condition despite the presence of various dynamics caused by fading, mobility and hidden terminals. Second, we design and implement a new Robust Rate Adaptation Algorithm (RRAA)that addresses the above challenge. RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, and an adaptive RTS filter to prevent collision losses from triggering rate decrease. Our extensive experiments have shown that RRAA outperforms three well-known rate adaptation solutions (ARF, AARF, and SampleRate) in all tested scenarios, with throughput improvement up to 143%.
11410811
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair-scheduling algorithms because of two unique characteristics of wireless media: (1) bursty channel errors and (2) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however, a base station has only a limited knowledge of the arrival processes of uplink flows. We propose a new model for wireless fair-scheduling based on an adaptation of fluid fair queueing (FFQ) to handle location-dependent error bursts. We describe an ideal wireless fair-scheduling algorithm which provides a packetized implementation of the fluid mode, while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless FFQ model.
1137858
Runtime Security Verification for Itinerary-Driven Mobile Agents
We present a new approach to ensure the secure execution of itinerary-driven mobile agents, in which the specification of the navigational behavior of an agent is separated from the specification of its computational behavior. We empower each host with an access control policy so that the host will deny the access from an agent whose itinerary does not conform to the host's access control policy. A host uses model checking algorithms to check if the itinerary of the agent conforms to its access control policy written in mu-calculus, and if so, grant access permission. In order to address the state explosion problem for model checking itineraries, we propose an approach called model generation code. In this approach, instead of verifying the itinerary itself, a host actually checks the conservative models of a mobile agent. If a conservative model does not satisfy the host's access control policy, the mobile agent will provide refined models for further verification. Our preliminary results show that this is a practical and promising approach to ensure the secure execution of mobile agents
611972
Tracking Causal Dependencies in an Active Object-Oriented Database
As active and deductive databases are applied to more complex domains (e.g. engineering design), the need to track the causality of data which has been derived by rules in the database becomes vital. Truth maintenance systems have been used in the area of artificial intelligence to track the causal dependencies of data derived from rules in knowledge-based systems. These same techniques can be applied to active object-oriented databases to provide the users with the means to track the relationships between data and rules. This paper describes the relevant features of a simple truth maintenance systems and puts forth a model of how truth maintenance systems can be integrated with an active object-oriented database, including the definition of new query operators to interpret the causal information for the end user.
24216233
CAQ: A machine learning tool for engineering
Abstract Machine learning algorithms developed from artificial intelligence (AI) research are rapidly finding useful applications in engineering domains. They are joining a family of tools that can help engineers summarize (or synthesize) massive amounts of data to support decision making. Traditional tools in this family, such as various statistical-based techniques, deal mostly with continuous (real) valued attributes — their results are relatively accurate, but often hard to interpret. On the other hand, logic-based learning tools, such as Michalski's AQ series of programs for learning concepts from examples, deal only with discrete valued attributes — their results are easier to comprehend, but not accurate for engineering applications which rarely deal solely with discrete valued attributes. Ideally, engineers need algorithms that work with a mix of attributes including those that take continuous values and those that take discrete values. Engineering problems also demand that learning algorithms be able to handle noise and produce concepts that are comprehensible. CAQ (Continuous AQ) is an algorithm designed to meet engineering requirements. This paper explains how CAQ combines continuous and discrete values, and shows that handling continuous attributes as real numbers instead of forcing them into a discrete representation leads to more efficient concept formation. Data from a turning process simulator used in support of machine operation planning in manufacturing are used to demonstrate the new algorithm.
6309018
Knowledge-based learning integrating acquisition and learning
Empirical learning algorithms are hampered by their inability to use domain knowledge to guide the induction of new rules. This paper describes knowledge-based learning, an approach to learning that selects the examples and relevant attributes for an empirical algorithm. Knowledge-based learning can be used for developing rules for engineering expert systems. Engineers often have some rules for problem solving, but also many experiences (examples) that facilitate solving problems. Knowledge-based learning systems are able to use both forms of knowledge.
41350051
Language engineering for the Semantic Web: a digital library for endangered languages