Collecting environmental sound by utilizing high-end mobile phones provides us opportunities to capture rich contextual information in real world. The gathered information can be used for various purposes, ranging from academic research to livelihood support. Furthermore, mobility of mobile phones opens a door for easily forming a dynamic sensing infrastructure, in order to gather fine-grained, but still large-scale data from both spatial and temporal perspectives. However, collecting, analyzing, storing, and sharing of sound data usually involve large energy consumption than scalar data, and like any battery-operated device, mobile phones also face the reality of energy constraints. Because people's first priorities are naturally to use mobile phones for their own purposes, there are occasions when people will not be inclined to allow their mobile phones to be used as sensing devices fearing that they will run out of batteries. Therefore, our research focuses on energy-efficient sensing, to reduce average energy consumption and to extend overall system lifetime. In this paper, we propose a node scheduling scheme for mobile nodes. By applying this scheme, optimized sensing schedules (ACTIVE/SLEEP duty cycles) will be periodically generated at each node. Following the provided schedule during sensing, energy-efficiency can be realized while original Quality of Service (i.e. coverage rate) is retained. Unlike most previous works which were based on ideal binary disk coverage model, our proposal is designed under a probabilistic disk coverage model which takes the characteristic of sound propagation into consideration. Furthermore, this is the first scheme that is adaptable to large-scale mobile sensor networks where topology dynamically changes. An accurate energy consumption model is adopted for evaluating the proposed scheme. Simulation results show that our scheme can reduce up to 48% energy consumption in an ideal environment and up to 31% energy consumption in a realistic environment. The robustness of our scheme is also verified against different type of sensing terrains and communication environments.

In this paper, we present a novel forwarding scheme to enhance communication stability based on geographic routing in mobile ad hoc networks, which is called "Position-based Heuristic Forwarding" (PHF). For alternative solutions to traditional ad hoc routings, many geographic routing algorithms have been proposed. Most of the existing routings impose a certain restriction, planarity, on the graph structure of network for delivering messages to destination definitely. PHF achieves the guaranteed packet delivery over Unit Disk Graph, which is more widely employed graph model for the study of ad hoc networks. Accordingly, to eliminate the restriction of the routing algorithms enhances the probability to deliver messages successfully in networks with high nodes' mobility rate. In the simulation of PHF, we have evaluated the performance comparisons between PHF and its related work, Greedy Perimeter Stateless Routing (GPSR) and Dynamic Source Routing (DSR), which are the prominent geographic and conventional topology-based routing protocols, respectively. The results show that PHF provides higher packet delivery success rate indicating better communication stability and equal or less overhead than these work.

In forthcoming home network environment, computation capability will be embedded invisibly in home appliances, sensors, walls, ceilings, and floors. People will conduct various tasks using multiple devices simultaneously without consciousness of using computers. In this paper, first, we propose an application model named Virtual Network Appliance (VNA) model which simplify and expand device utilization. In the model, each device has VNA runtime system and function objects, called VNA components, running on it. A user task is defined in an application called VNA which is a logical appliance consisting of abstract function requirements and a message graph among them. Second, we propose Virtual Plug&Play mechanism which is a dynamic service integration mechanism in VNA model implementation. When a user conducts a task, he/she makes a VNA runtime system on a user-side terminal load a VNA definition appropriate for the task. Virtual Plug&Play dynamically discovers required VNA components and establishes the message graph as defined. Since XML documents are used to describe a VNA, users can share and customize it easily. We call the device integration done by Virtual Plug&Play top-down integration, which existing middleware do not aim at. Finally, we show that Virtual Plug&Play affords practical performance for top-down integration by performance evaluation.

When multiple flows including continuous media streams are simultaneously sent from a computer, allocation and management of both processor capacity and network bandwidth need to be considered. We propose a framework of Quality of Service (QoS) management inside a sending host that controls execution of sending threads in consideration of utilization of processor capacity and network bandwidth. To distinguish from flows which require only best-effort service, we call a flow which requires a specific rate of service "reserved flow. " To guarantee QoS of such reserved flow both in processor- and network-intensive cases in a sending host, processor capacity reserve is allocated such that the rate of each reserved flow is attained and non-conforming data are policed before they are transmitted. Processor Capacity Manager and the network device driver exchange information in a cooperative manner to support the rate adaptive allocation of processor capacity reserve. In this paper, we describe design and implementation of our framework on RT-Mach. The results of performance evaluations demonstrate that our scheme performs well for full-duplex Ethernet.

In this paper, we present Scalable Data Collection (SDC) protocol, a tree-based protocol for collecting data over multi-hop, wireless sensor networks. The design of the protocol aims to satisfy the requirements of sensor networks that every sensor transmits sensed data to a sink node periodically or spontaneously. The sink nodes construct the tree by broadcasting a HELLO packet to discover the child nodes. The sensor receiving this packet decides an appropriate parent to which it will attach, it then broadcasts the HELLO packet to discover its child nodes. Based on this process, the tree is quickly created without flooding of any routing packets. SDC avoids periodic updating of routing information but the tree will be reconstructed upon node failures or adding of new nodes. The states required on each sensor are constant and independent of network size, thereby SDC scales better than the existing protocols. Moreover, each sensor can make forwarding decisions regardless of the knowledge on geographical information. We evaluate the performance of SDC by using the ns-2 simulator and comparing with Directed Diffusion, DSR, AODV, and OLSR. The simulation results demonstrate that SDC achieves much higher delivery ratio and lower delay as well as scalability in various scenarios.

Traffic management schemes such as Connection Admission Control (CAC), policing, and traffic shaping are important to provide multimedia communications with better Quality of Service (QoS). In the conventional model, admission control and policing are done at intermediate nodes, and traffic shaping is done at the edge of a network. However, QoS of communications should be defined between tasks or threads rather than between hosts. Therefore traffic management inside a host is as important as that in networks. We propose software-based traffic management architecture over a real-time microkernel. The architecture focuses on the interface between a network driver and user threads calling the driver. We categorized services of communication threads into three classes: Real-Time at Guaranteed Rate (RT-GR), Real-Time at Available Rate (RT-AR), and Best-Effort (BE). Our architecture is designed for an environment containing a mixture of these services. In the architecture, a sender periodic thread of RT-GR or RT-AR is executed such that the sending rate matches a user-specified rate. The network driver monitors the per-flow rate of injected data and discards the data if the injected rate exceeds the user-specified rate. To avoid the continuous discarding of data, the sending thread can adjust its sending rate by periodically looking at logged data concerning the rate. RT-AR service can achieve more than the specified rate when bandwidth is available. The scheme of software traffic management is effective in attaining higher throughput not only for full-duplex Ethernet but also for ATM because the difference of rate between hardware and software is reduced. In this paper, we describe the design and implementation of the software-based traffic management architecture on Real-Time Mach. The results of performance evaluations demonstrate that our traffic management scheme performs well for full-duplex Ethernet.

Because of the large scale of wireless sensor networks, the configuration needs to be done autonomously. In this paper, we present Scalable Data Collection (SDC) protocol, a tree-based protocol for collecting data over multi-hop, wireless sensor networks. The design of the protocol aims to satisfy the requirements of sensor networks that every sensor transmits sensed data to a sink node periodically or spontaneously. The sink nodes construct the tree by broadcasting a solicit packet to discover the child nodes. The sensor receiving this packet decides on an appropriate parent to which it will attach, it then broadcasts the same packet to discover its child nodes. Through this process, the tree is created autonomously without any flooding of the routing packets. SDC avoids periodic updating of routing information but the tree need to be reconstructed upon node failures or adding of new nodes. The states required on each sensor are constant and independent of network size, therefore SDC scales better than the existing protocols. Moreover, each sensor can make forwarding decisions regardless of the knowledge on geographical information. We evaluated the performance of SDC by using the ns-2 simulator and comparing with Directed Diffusion, DSR, AODV, and OLSR. The simulation results demonstrate that SDC achieves much higher delivery ratio, shorter delay, as well as high scalability in various scenarios.

Portable sensory devices such as sensors equipped mobile phones enable convenient sensing and monitoring of urban areas. Such devices, which are always carried by humans, are referred to as Human Probes. Instead of carrying out sensing activities independently, cooperation of Human Probes helps in realizing efficient urban sensing environments. In this paper, we propose an Architecture of Qualitative Urban Information Blending and Acquisition (Aquiba), in which the sensing activities are adjusted autonomously according to cooperation of Human Probes. Aquiba introduces a cooperative sensing approach which aims to maintain desired sensing resolution efficiently while minimizing overall energy consumption. To study the performance of Aquiba, we have conducted comprehensive simulations ranging from small- to large-scale scenarios along with applying three different movement patterns of human. The simulation results demonstrate that Aquiba is capable of providing high sensing resolution and reducing overall energy consumption.

Recently there has been a great deal of research on using mobility in sensor networks to assist their sensing tasks. In this paper, we propose a policy-based session control protocol for Multi-Robot Sensor Networks (MRSNs) called Billiards. In a MRSN, all messages are transported by the physical motion of participants (mobile nodes) in the network. When a large volume of data or continuous data is required to be transferred, there exists a problem determining how the data is fragmented and how the mobile nodes are formed for carrying the data to the destination. To overcome the issues, we propose a suitable method of session control which is determined based on a state of surrounding mobile nodes such as number, maximum-velocity and buffer-size. Billiards also takes a system policy of delay minimization into consideration. In this paper, we describe the protocol and model of Billiards and analyze the model. We evaluated the performance of Billiards utilizing mobile robots which are equipped with MICA2 mote and comparing with non optimized method. The experimental results demonstrate that Billiards achieves less delay than non optimized method at every velocity and buffer-size of each robot.

This paper presents a path compression protocol for on-demand ad hoc network routing protocols, which is called dynamic path shortening (DPS). In DPS, active route paths adapt dynamically to node mobility based on the "local" link quality estimation at each own node, without exchanging periodic control packets such as Hello messages. Each node monitors its own local link quality only when receiving packets and estimates whether to enter the "proximity" of the neighbor node to shorten active paths in a distributed manner. Simulation results of DPS in several scenarios of various node mobility and traffic flows reveal that adding DPS to DSR which is the conventional prominent on-demand ad hoc routing protocol significantly reduces the end-to-end packet latency up to 50-percent and also the number of routing packets up to 70-percent over the pure DSR, in heavy traffic cases. We also demonstrate the other simulation results obtained by using our two novel mobility models which generate more realistic node mobility than the standard random waypoint mobility model: Random Orientation Mobility and Random Escape Mobility models. Finally, simple performance experiments using DPS implementation on FreeBSD OS demonstrate that DPS shortens active routes in the order of milliseconds (about 5 ms).