Increasing real estate and other infrastructure costs have resulted in the trend of co-working offices where users pay as they use for individual desks. Co-working offices that provide personalized comfort need to address users with potentially widely varying thermal comfort preferences. Providing personalized comfort in cabins separated by physical partitions with neighboring thermal zones or open-plan offices with a single actuator has received attention in the literature. In this article, the problem of minimizing user discomfort in open-plan co-working offices with multiple actuators while being cognizant of the energy consumed is considered. Specifically, the decision problems of assigning users to desks based on their thermal preferences and jointly controlling the multiple actuators are addressed. The non-linearities in the underlying thermodynamic constraints and the seating decision together make the problem computationally hard. A two-step heuristic that addresses these issues is presented. First, using a model that accounts for spatio-temporal thermodynamics, a one-time assignment of users to desks is performed that reduces the thermal resistance faced by the HVAC systems to provide the preferred comfort levels. Next, the setpoints are decided for all actuators to jointly minimize user discomfort by optimization and model-predictive control. Further, scalability is addressed by clustering user preferences and the associated HVAC actuators’ setpoints for the cases where a large number of actuators may be present in the room.

Predicting travel times of vehicles in urban settings is a useful and tangible quantity of interest in the context of intelligent transportation systems. We address the problem of travel time prediction in arterial roads using data sampled from probe vehicles. There is only a limited literature on methods using data input from probe vehicles. The spatio-temporal dependencies captured by existing data driven approaches are either too detailed or very simplistic. We strike a balance of the existing data driven approaches to account for varying degrees of influence a given road may experience from its neighbors, while controlling the number of parameters to be learnt. Specifically, we use a NoisyOR conditional probability distribution (CPD) in conjunction with a dynamic Bayesian network (DBN) to model state transitions of various roads. We propose an efficient algorithm to learn model parameters. We also propose an algorithm for predicting travel times on trips of arbitrary durations. Using synthetic and real world data traces we demonstrate the superior performance of the proposed method under different traffic conditions.

Sink trees such as Breadth-First Search (BFS) or Shortest-Path Tree (SPT) are essential in Wireless Sensor Networks (WSNs) for various purposes such as data gathering, aggregation, clustering, and synchronization. These trees minimize the path-lengths reachable from root node to any other node in the network. With the energy-bound sensor nodes, it is vital to construct such trees in an effective manner, by minimizing the number of message exchanges. By exploiting the broadcast nature of the underlying wireless medium, we present distributed energy-efficient algorithms for constructing BFS and SPT sink trees in WSNs. To mitigate collisions, we propose a simple distributed collision avoidance mechanism that enables efficient functioning of our tree construction algorithms. Extensive simulation study is performed for different networks by varying the size, degree, and depth. Our promiscuous learning based algorithm outperformed by incurring up to 66% less (message) exchanges than the state-of-the-art tree construction algorithm.

Data gathering is a typical operation in wireless sensor networks where data flow through a data gathering tree towards a sink node. Plenty of work had been done on constructing energy-efficient data gathering trees at the routing layer. However, data generation in wireless sensor networks could be bursty as it is driven by the events of interest. Without any sleep scheme, the sensor nodes will stay idle for most of the time. Therefore energy-efficient data gathering trees alone are not enough for energy saving. We propose a routing layer data gathering sleep scheme (DGSS) which could be incorporated into existing data gathering tree formation algorithms to save unnecessary energy consumption due to idle listening and meanwhile adapts to bursty traffic condition. We compare DGSS with DMAC, a popular energy efficient MAC protocol for data gathering, through simulations and show that DGSS can perform better than DMAC for bursty traffic at relatively high data rates.

DMAC is a popular data gathering MAC protocol for wireless sensor networks. It employs staggered sleep-awake schedules to enable continuous data forwarding along a data gathering tree, resulting in reduced end-to-end delays and energy consumption. In this paper we present a generalized model for the DMAC protocol and for this generalized model we have analyzed end-to-end delay and energy consumption with respect to the source node for both constant bit rate traffic and stochastic traffic following a Poisson process. The stochastic traffic scenario is modeled as a discrete time Markov chain and expressions for state transition probabilities, average delay and average energy consumption are developed and it is shown that these can be evaluated numerically. Simulations are carried out with various parameters and the results are in line with the analytical results. Both analysis and simulations indicate that DMAC is more suitable for constant bit rate traffic than stochastic traffic.

Virtual world and other collaborative applications are increasingly becoming popular among Internet users. In such applications, users interact with each other through digital entities or avatars. In order to preserve the user experience, it is important that certain Quality of Service (QoS) requirements (e.g., delay and bandwidth) are satisfied by the interactions. These QoS requirements are usually defined by the application designer. When applications with such QoS requirements are being deployed on a network of servers, an appropriate set of servers capable of satisfying the QoS constraints of the interactions must be identified. This identification process is nothing, but the subgraph homeomorphism problem. In this paper, we present polynomial-time solutions for a special case of this problem viz. subtree homeomorphism problem, wherein the guest and the host graphs are both trees. We also discuss generalizations of the subtree homeomorphism problem and present polynomial-time solutions.

Consider a wireless sensor network where each node has K radios r1,r2, ⋯ , rKsuch that the one hop reachability distance (resp. energy expended) of (resp. by) radio riis greater than that of rj1 ≤ j <; i ≤ K. Given such a network, the problem of energy efficient radio activation is to minimize the total energy spent by the active radios across all nodes in order to maintain a connected network. We show that this problem is NP-Hard. We initially pay attention to the case of K = 2 and discuss a basic version of the radio activation problem in such networks. We propose approximation methodologies for solving this problem. Our analytical and experimental studies reveal that the greedy algorithm and the minimum spanning tree solution have the best worst case performance while the greedy algorithm has the best average case performance. To the best of our knowledge, this is one of the first few works to focus on optimal radio activation in generic multi-radio wireless networks.

Wireless Sensor Networks (WSNs) open up wide range of possibilities for new applications such as monitoring and surveillance applications due to their low-cost and easy deployability. However, the limitations in terms of limited CPU processing power, memory, and battery, bring in a great deal of challenge to provide adequate security for on-board data storage and communication. While many works on secure key establishment exist, most of them assume that sensor nodes are either in fixed location or move within a single WSN. As WSN technology develops, there are more applications coming up which require a sensor node to roam across multiple WSNs. This paper presents a roaming protocol that provides security for the on-board sensory data (in terms of data access) while allowing a sensor node to move across multiple WSNs.

Data generation in wireless sensor networks could be bursty as it is dictated by the presence or absence of events of interest that generate these data. While conventional sensor nodes possessed only one radio interface, next generation sensor nodes are expected to have two (possibly more) radio int

We can improve the end-to-end throughput between a sender and receiver in a wireless network using multiple paths which do not interfere with each other. Given finding such paths is computationally hard, we present a heuristic that is amenable to distributed implementation. This heuristic allows for the possibility of interfering links but schedules the transmission in ways to achieve the maximum possible throughput. One can characterize interfering links as either destructive or non-destructive, the latter of which does not affect the throughput, if transmission is properly scheduled. We present a distributed algorithm which exploits this knowledge to find multiple s-t paths such that high throughputs could be achieved despite the interference. On a wireless network with n nodes, our distributed algorithm has a time and message complexity of O(n2).

This paper outlines the design and development of a low-cost, small-footprint wireless sensor capable of sampling and transmitting sensory data at frequencies more than 6000 Hz. This sensor has been designed and developed in-house using off the shelf components and open source software for container integrity monitoring. The paper presents details of the various refinements that have been carried out to improve the default performance of the sensory unit. Laboratory tests indicate that while the developed sensor has comparatively higher power consumption than other commercially available sensory units, its small form factor and low cost make it attractive enough for several applications. The paper then describes how these sensors can be used to realize a reliable, round-the-clock system for monitoring the stability and integrity of cargo containers.

There has been a growing interest in designing mobile systems consisting of special relay nodes whose mobility can be controlled by the underlying network. In this paper, we consider the design of a heterogeneous mobile ad hoc network (MANET) consisting of two kinds of mobile nodes-traditional nodes with limited energy and a few controllable mobile relay nodes with relatively abundant energy resources. We propose a novel relay deployment framework that utilizes mobility prediction and works in tandem with the underlying MANET routing protocol to optimally define the movement of the relay nodes. We present two instances of the relay deployment problem, together with the solutions, to achieve different goals. Instance 1, termed Min-Total, aims to minimize the total energy consumed across all the traditional nodes during data transmission, while instance 2, termed Min-Max, aims to minimize the maximum energy consumed by a traditional node during data transmission. Our solutions also enable the prioritization of individual nodes in the network based on residual energy profiles and contextual significance. We perform an extensive simulation study to understand the trade-offs involved in deploying an increasing fraction of such relay nodes in the network. We also investigate the performance of the proposed framework under different mobility prediction schemes. Results indicate that even when the relay nodes constitute a small fraction of the total nodes in the network, the proposed framework results in significant energy savings. Further, we observed that while both the schemes have their potential advantages, the differences between the two optimization schemes are clearly highlighted in a sparse network.

One of the most critical issues in wireless sensor networks is the limited availability of energy within the network nodes. Recently, the idea of deploying a high capacity overlay using virtual sinks with long range 802.11 links to ease congestion in the underlying sensor network has been explored. Since the VSs are battery powered, it is important to conserve energy in them too. To reduce the energy consumption, usually the shortest path (SP) route is preferred in networks that do not use topology control. However, if only a few of the VS nodes are sending data, routing along the SP may require some additional VS nodes to be turned on just for the relaying purpose which otherwise could be turned off. Since the link bandwidth is high in 802.11 (Mbps) and the sensory data generation rate is low (Kbps) in comparison to the bandwidth, a high idle-mode energy cost may be incurred in the relaying VS nodes. In this paper, we explore the idea of using minimum connected dominating set (MCDS) based routes, since more energy can be saved by switching the non-dominator VSs to sleep mode and by funneling all the data through the MCDS nodes. We propose an energy-aware routing scheme that considers both the SP route and the MCDS nodes to discover a path along the VS network to the physical sink. Performance evaluation of the routing scheme shows a notable reduction in the overall energy consumption in the network with respect to SP routing while simultaneously maintaining an acceptable packet delivery rate.

This paper proposes a new approach for biologically inspired computing on the basis of Gene Regulatory Networks. These networks are models of genes and dynamic interactions that take place between them. The differential equation representations of such networks resemble neural networks as well as idiotypic networks in immune system. Although several potential applications have been outlined, an example, the problem of placing sensors optimally in a distributed environment is considered in detail. A comparison with NSGA-II suggest that the new method is able to accomplish near-optimal coverage of sensors in a network.

Wireless sensor networks (WSNs) are considered to be an ideal solution for many commercial and industrial applications due to their low-cost and easy deployability. However, Security is a critical concern in WSNs due to the technical challenge of providing sufficient security with battery-powered sensors that have limited computational resources. Although numerous advancements have been made in the field of key management in WSNs, most have focused on establishing keys within a single WSN. In addition, many have assumed that the locations of the sensors are fixed. As the number of WSN applications increases, there is an increasing demand for solutions that allow sensors to securely roam between different WSNs even when the WSNs are managed by independent organizations. This paper presents a base station-to-sensor pairwise key management protocol that allows sensor nodes to relocate to other WSNs as required by the application. In addition, the proposed solution localizes the damage that can arise when a sensor or a base-station is compromised without increasing the computational burden on the sensors. To the best of our knowledge, this is one of the first few works to address the pairwise key distribution problem in WSNs that allow nodes to roam between different, independent networks.

We can improve the end-to-end throughput between a sender and receiver in a wireless network using multiple paths which do not interfere with each other. Given that the problem of finding such paths is computationally hard, the paper focuses on finding multiple paths which may have interference between them, but still are able to obtain the maximum possible throughput. It is achieved by observing that the pattern of interference is more important than the number of interfering links. The nature of path sets with non-destructive interference is discussed and based on these observations, combinatorial techniques for finding interference aware disjoint paths in a wireless network are presented. Simulation results indicate that the proposed solutions achieve throughputs that are significantly higher than the established theoretical results.

Collaborative multimedia applications (CMAs) on overlay networks are gaining popularity among users who are geographically dispersed. Examples of these kinds of applications include networked games and collaborative design and simulation. An important challenge in realizing CMAs is obtaining floor control, a problem in which the end-users compete among themselves to gain exclusive access to a shared resource. In this paper, we present deterministic and randomized distributed mechanisms for solving the floor control problem. In particular, we adapt the well-known MAC protocols viz. distributed queue dual bus (DQDB), ALOHA, and carrier sense multiple access (CSMA) as solutions for the floor control problem. Central to our adaptation is an algorithmic methodology that efficiently virtualizes the underlying network connecting the CMA participants so as to enhance the proposed solutions' performance. We present analytical and experimental studies on the performance of the proposed floor control protocols that bring out their essential characteristics.

Online energy aware routing in wireless networks is the problem of finding energy efficient routes that maximize the network lifetime without the knowledge of future message flows. To maximize network lifetime, the paths for message flows are chosen in such a way that the total energy consumed along the path is minimized while avoiding energy depleted nodes. Finding paths which consume minimum energy and finding paths which do not use energy depleted nodes lead to conflicting objectives. In this paper, we propose a two-phased energy-aware routing strategy that balances these two conflicting objectives by transforming the routing problem into a multi-metric widest path problem. We find that the proposed approach outperforms the best known algorithm in literature. We also demonstrate a simple but insightful relationship between the total energy required along a path and the minimum remaining energy of a node along the path.

In recent years, there has been a growing interest in designing mobile systems consisting of special relay nodes whose mobility can be controlled by the underlying network. In this paper, we consider the design of a heterogeneous mobile ad hoc network (MANET) consisting of two kinds of mobile nodes - the traditional nodes with limited energy and a few mobility controllable relay nodes with relatively abundant energy resources. We propose the relay deployment problem that aims to optimally position these relay nodes in the network so as to minimize the overall power consumption for data transmission at the traditional nodes. We present a mobility prediction based framework to solve to the relay deployment problem in a truly mobile network. We investigate the performance of the proposed framework through extensive simulation study using three different mobility prediction schemes. We also perform experiments to understand the tradeoffs involved in deploying an increasing fraction of such relay nodes in the network. Results indicate that even when the relay nodes constitute a small percentage of the total nodes in the network, the proposed framework results in significant energy savings.

In this paper, we introduce a framework termed Accelerated Frame Slotted Aloha (AFSA) for reducing the average reading time of passive RFID tags in dense environments. The proposed framework can be used in conjunction with almost all tag reading protocols that are based on frame slotted Aloha. AFSA reduces the tag reading time by decreasing the time wasted due to collisions and idle slots. We also discuss extensions of AFSA to read passive tags in a mobile setting. Simulation results show that AFSA can significantly reduce the average tag reading time with respect to the base protocol under both static and mobile settings.

Many protocols have been proposed separately for ad hoc networks from an energy efficiency or a security perspective. In this paper we propose a novel integrated protocol for improving both energy efficiency and security. The proposed sector-based clustering and routing (SBCR) protocol increases the survivability of the network and also provides better security due to multipath routing. Nodes requiring higher levels of security have more routing options available than nodes with lower levels of security

Quality-of-service (QoS) routing between domains is an essential component for providing service differentiation in the Internet. State aggregation is a technique that makes QoS routing scalable to large internetworks, by presenting a concise and accurate representation of the domain to the routing process. The concept of using a domain's routing capacity as a bandwidth aggregate has been in existence for some time. However, no methodology has been suggested in the literature for its estimation and usage. Also, the impact of a domain's routing capacity on the routing performance has not been studied before. This paper aims to fill these voids by presenting a framework based on "network flows" for estimating a domain's routing capacity and evaluating its efficacy on the routing performance. The routing capacity is used in conjunction with the conventional widest path bandwidth as the domain aggregate. Analytical and experimental results show that appropriate use of routing capacity along with the widest path bandwidth reduces the tendency of the advertised aggregate to overestimate bandwidth availability, and makes the routing process more robust to the frequency of domain state updates. During periods of congestion, the use of routing capacity can improve the bandwidth admitted into the network by as much as 20%

Quality of service (QoS) routing between domains is indispensable for deploying QoS in the Internet. State aggregation is a technique that makes QoS routing scalable to large networks. As the impreciseness in the advertised aggregate adversely affects the performance of the QoS routing process, it is important to investigate the accuracies of various aggregation schemes. In this paper, we study the efficacy of a new bandwidth aggregation scheme, and compare our scheme's performance with that of the existing schemes. Our analytical and experimental studies show that for active networks, the proposed aggregation scheme is more accurate, and gives a better routing performance than the current schemes.

QoS routing is the process of routing a connection based on the connection's resource requirements. The overhead involved in QoS routing increases with the network size. State aggregation is an important technique that makes QoS routing scalable. We propose a new domain state aggregation technique based on "network-flows", for stochastic networks. We propose a new fast heuristic algorithm to estimate the PMF of "maximum-flow" through a probabilistic flow network. Using this algorithm, we aggregate the bandwidth information in a domain and use it along with the path aggregate for routing. Through simulations, we show that stochastic estimation of traffic capacity is better than deterministic estimation and gives a better bandwidth admission ratio when compared with existing state aggregation techniques.

This paper presents the design principles of dynamic service negotiation protocol (DSNP). DSNP is a protocol to negotiate the SLS (service level specification) in the IP layer. It can be used for service negotiation from host to network, network to host, and network to network. The automated negotiation makes service negotiation efficient in terms of time, cost, and correctness. The dynamic negotiation not only allows users to adapt their needs dynamically, but also lets providers utilize the network better. DSNP can be used in both wireline and wireless networks. It is, however, particularly useful in the mobile environment. To demonstrate the usefulness of DSNP, a reference wireless QoS architecture based on DiffServ is presented. Example applications and experimental results are illustrated.

QoS routing is the process of routing a connection based on the connection's resource requirements. The overhead involved in QoS routing increases with the network size. State aggregation is an important technique that helps to reduce the overhead. We propose a new state aggregation technique based on "network-flow". Our approach allows a domain to update the aggregate sent by other domains and keep track of resource availability in other domains. We study the efficacy of our approach with respect to various network and traffic parameters. Preliminary simulation results show that our approach gives a better bandwidth admission ratio when compared with existing techniques.

Multimedia applications such as video-conferencing, telemedicine, HDTV, etc. have very stringent quality-of-service (QoS) demands and require a connection-oriented service. For these applications, a path satisfying their requirements in terms of bandwidth, delay buffer, etc. needs to be found. As conventional IP routing is based only on hop counts, it is not suitable for multimedia applications. It is clear that, to route requests that have QoS requirements, existing routers should be made QoS aware and the packet forwarding should be based on QoS parameters. Also, routing protocols like OSPF and RIP must be extended suitably to facilitate QoS routing. The goal of QoS routing algorithms is to find a loop-less path satisfying a given set of constraints on parameters like bandwidth, delay, etc. The path selection process could return either the entire path to the destination or the best next hop for the request. The first case is called "source routing" and the second is referred to as "distributed routing". In this paper, we propose a new distributed QoS routing algorithm for unicast flows, which has a very low call establishment overhead. Our algorithm makes use of existing IP routing protocols such as OSPF and RIP with minimal modifications.

The goal of QoS routing is to find a loopless path through a network that can satisfy a given set of constraints on parameters such as bandwidth, delay and cost. QoS routing algorithms can be classified into three categories. They are source routing, distributed routing and hierarchical routing. In this paper we propose a distributed QoS routing algorithm that gives high call admission rates in a congested network for constraints on metrics like bandwidth, buffer, and CPU usage with a low message complexity.