Kenneth N. Brown

ER-MAC: A Hybrid MAC Protocol for Emergency Response Wireless Sensor Networks

This paper introduces ER-MAC, a hybrid MAC protocol for emergency response wireless sensor networks. ERMAC is designed as a hybrid of the TDMA and CSMA approaches, giving it the flexibility to adapt to traffic and topology changes. It adopts a TDMA approach to schedule collision-free slots. Nodes wake up for their scheduled slots, but otherwise switch into power-saving sleep mode. When an emergency occurs, nodes that participate in the emergency monitoring change their MAC behaviour by allowing contention in TDMA slots to achieve high delivery ratio and low latency. ER-MAC offers a synchronised and loose slot structure to allow nodes to join or leave the network. Simulations in ns-2 show that ERMAC outperforms Z-MAC with higher delivery ratio, lower latency, and lower energy consumption.

Modelling Interference Temperature Constraints for Spectrum Access in Cognitive Radio Networks

With the advent of cognitive radio technology, new paradigms for spectrum access can achieve near-optimal spectrum utilisation by letting each user sense and utilise available spectrum opportunistically while regulating the interference it imposes on other users through interference constraints. However, the simplest and most common forms of such constraints are binary and transmitter-centric, which are often inefficient since they only consider pair-wise sets of transmitters. Hence, we propose a non-binary receiver-centric constraint model for spectrum access in cognitive radio networks. Such a model is in line with the recently proposed interference temperature metric that constraints whole subsets of transmitters, thereby permitting interfering signals to be introduced and enabling additional communication, leading to improved spectrum utilisation. These constraints are easy to generate and check, and are currently being used to devise a co-operative negotiated etiquette for cognitive radios offering heterogeneous services in a wireless office networking scenario.

Scheduling with uncertain durations: Modeling β-robust scheduling with constraints

Many real-world scheduling problems are subject to change, and scheduling solutions should be robust to those changes. We consider a single-machine scheduling problem where the processing time of each activity is characterized by a normally distributed random variable, with flowtime as the main solution criterion. The objective is to find the @b-robust schedule-the schedule that minimizes the risk of the flowtime exceeding a threshold. We show how to represent this problem as a constraint model, explicitly representing the uncertainty and robustness as input parameters and objectives, and enabling the uncertainty to propagate using constraint propagation. Specifically, we develop three models (primal, dual and hybrid), and we show the effect of dominance rules on the search space.

Optimized process planning by generative simulated annealing

Manufacturing process planning is a difficult problem with a prohibitively large search space. It is normally tackled by decomposing goal objects into features, and then sequencing features to obtain a plan. This paper investigates an alternative approach. The capabilities of a manufacturing process are represented by a formal language of shape, in which sentences correspond to manufacturable objects. The language is interpreted to describe process plans corresponding to the shape generation, complete with cost estimates. A macro layer that describes single operations of the machine is implemented on top of the formal language. The space it describes is searched by the generative simulated annealing algorithm, a stochastic search technique based on simulated annealing. Plans that are close to the optimum are generated in reasonable time.

A Dynamic Model for Fire Emergency Evacuation Based on Wireless Sensor Networks

This work introduces a dynamic model for the fire emergency evacuation problem. The model extends the concept safety introduced by Barnes et.al. for the situation when the navigation graph is dynamic. The two possible scenarios are described for using the dynamic model with a Wireless Sensor Network for fire emergency evacuation.

Grammatical design

Design can be regarded as the process of transforming an initial set of requirements (and possibly an initial design) into an explicit, complete specification of an object that satisfies those requirements. The designers task involves repeated cycles of considering an existing partial design, comparing it with the design goal, deciding on a transformation to get closer to the goal, and then applying that transformation to the partial design. A transformation may take one of various forms, including adding detail to a design, modifying an existing structure, or adding new components. Grammatical design is a paradigm based directly on this view, concentrating on the representational structures and underlying transformation mechanisms. A grammar, or a formal generative system, has three parts: a vocabulary of elements; a set of transformation rules that transform structured arrangements of the elements into new structures; and an initial structure. The paper considers how a grammar, or a formal generative system, can provide design support.

Features aka the semantics of a formal language of manufacturing

Features are application and viewer-dependent interpretations of geometry. This article demonstrates how the notion of features arising out of geometric data may be formalised as the semantics of a language of shape, using machining operations as an extended example. The syntax and semantics of formal languages are discussed, with particular reference to their use in design. A simplified lathe is defined, and a parametric attributed set grammar is presented which specifies the range of shapes manufacturable on that lathe. A simple feature space is then defined, in which feature models representing those shapes may be constructed. The link between the shapes and the feature models is then formalised as the semantics of the grammar using description functions, and it is shown how the feature models develop as shape generation proceeds. Finally, some implications of this work for feature-based design and manufacturing are discussed.

A hybrid MAC protocol for emergency response wireless sensor networks

Abstract We introduce ER-MAC, a novel hybrid MAC protocol for emergency response wireless sensor networks. It tackles the most important emergency response requirements, such as autonomous switching from energy-efficient normal monitoring to emergency monitoring to cope with heavy traffic, robust adaptation to changes in the topology, packet prioritisation and fairness support. ER-MAC is designed as a hybrid of the TDMA and CSMA approaches, giving it the flexibility to adapt to traffic and topology changes. It adopts a TDMA approach to schedule collision-free slots. Nodes wake up for their scheduled slots, but otherwise switch into power-saving sleep mode. When an emergency occurs, nodes that participate in the emergency monitoring change their MAC behaviour by allowing contention in TDMA slots to achieve high delivery ratio and low latency. In its operation, ER-MAC prioritises high priority packets and sacrifices the delivery ratio and latency of the low priority ones. ER-MAC also guarantees fairness over the packets’ sources and offers a synchronised and loose slot structure to allow nodes to join or leave the network. Simulations in ns-2 show the superiority of ER-MAC over Z-MAC, a state-of-the art hybrid MAC protocol, with higher delivery ratio, lower latency, and lower energy consumption. When a cluster of nodes in the network detects fire, nodes with ER-MAC deliver twice as many high priority emergency packets and four times faster than Z-MAC. This is achieved by ER-MAC with only one fifth as much energy as Z-MAC.

Cognitive radio for disaster response networks: survey, potential, and challenges

In the wake of a natural or man-made disaster, restoration of telecommunications is essential. First responders must coordinate their responses, immediate casualties require assistance, and all affected citizens may need to access information and contact friends and relatives. Existing access and core infrastructure may be damaged or destroyed, so to support the required services, new infrastructure must be rapidly deployed and integrated with undamaged resources still in place. This new equipment should be flexible enough to interoperate with legacy systems and heterogeneous technologies. The ability to selforganize is essential in order to minimize any delays associated with manual configuration. Finally, it must be robust and reliable enough to support mission-critical applications. Wireless systems can be more easily reconfigured than wired solutions to adapt to the various changes in the operating environment that can occur in a disaster scenario. A cognitive radio is one that can observe its operating environment, make decisions and reconfigure in response to these observations, and learn from experience. This article examines the use of cognitive radio technologies for disaster response networks and shows that they are ideally suited to fulfill the unique requirements of these networks. Key enabling technologies for realizing real-world cognitive radio networks for disaster response are discussed and core challenges are examined.

Analysis of smartphone user mobility traces for opportunistic data collection in wireless sensor networks

The increasing ubiquity of smartphones coupled with the mobility of their users will allow the use of smartphones to enhance the operation of wireless sensor networks. In addition to accessing data from a wireless sensor network for personal use, and the generation of data through participatory sensing, we propose the use of smartphones to collect data from sensor nodes opportunistically. For this to be feasible, the mobility patterns of smartphone users must support opportunistic use. We analyze the dataset from the Mobile Data Challenge by Nokia, and we identify the significant patterns, including strong spatial and temporal localities. These patterns should be exploited when designing protocols and algorithms, and their existence supports the proposal for opportunistic data collection through smartphones.