Delay Tolerant Network (DTN) has been emerged to support the network connectivity of the disruptive networks. A variety of routing methods have been proposed to reduce the latency for message delivery. PROPHET was proposed as a probabilistic routing that utilizes history of encounters and transitivity of nodes, which is computed as contact probability. While PROPHET improves the performance of DTN due to contact probability, contact probability is just one parameter reflecting the mobility pattern of nodes, and further study on utilizing contacting information of mobility pattern is still an important problem. Hence, in this paper, we try to improve routing for DTN by using a novel metric other than contact probability as mobility information. We propose the routing protocol to use mean residual contact time that describes the contact period for a given pair of nodes. The simulation results show that using the mean residual contact time can improve the performance of routing protocols for DTN. In addition, we also show in what situations the proposed method provides more efficient data delivery service. We characterize these situations using a parameter called Variation Metric.

Named Data Networking (NDN) is a promising architecture for the future Internet and it is mainly designed for efficient content delivery and retrieval. However, producer mobility support is one of the challenging problems of NDN. This paper proposes a scheme which aims to optimize the tunneling-based producer mobility solution in NDN. It does not require NDN routers to change their routing tables (Forwarding Information Base) after a producer moves. Instead, the Interest packet can be sent from a consumer to the moved producer using the tunnel. The piggybacked Data packet which is sent back to the consumer will trigger the consumer to send the following Interest packets through the optimized path to the producer. Moreover, a naming scheme is proposed so that the NDN caching function can be fully utilized. An analysis is carried out to evaluate the performance of the proposal. The results indicate that the proposed scheme reduces the network cost compared to related works and supports route optimization for enhanced producer mobility support in NDN.

Due to the limited resources of sensor nodes, an energy-efficient routing algorithm of Wireless Sensor Networks is considered as one of the most important issues in improving network lifetime. To resolve this issue, several routing algorithms have been suggested, but the published studies have mainly focused on minimizing distances between sensor nodes or the number of hops. These researches have also assumed that all the sensor nodes participate in the sensing task. In this paper, we propose a new cluster head selection algorithm focusing on both the density of sensor nodes and sensing-awareness that has not been considered yet in other existing researches on cluster-based routing scheme. In the real sensor network environment, only a part of sensor nodes participates in data reporting, so consideration of sensing-awareness in a routing algorithm will have effect on network efficiency. Moreover, the density of sensor nodes that has resulted from geographical location of sensor nodes can be an important factor in cluster head selection. The simulation results show that the proposed algorithm, by considering these 2 factors simultaneously, reduces energy consumption and enhances network lifetime.

With Wireless Sensor Networks (WSNs) involving in diverse applications, the realistic analysis of energy consumption of a sensor node in an error-prone network environment is emerging as an elementary research issue. In this paper, we introduce a Distributed Communication Model (DCM) that can accurately determine the energy consumption through data communication from source to destination in error-prone network environments. The energy consumption is affected with the quality of link, which is characterized by symmetry, directivity, instability, and irregularity of the communication range of a sensor node. Due to weak communication links, significant packet loss occurs that affects the overall energy consumption. While other models unable to determine energy consumption due to lossy links in error-prone and unstable network environments, DCM can accurately estimate the energy consumption in such situations. We also perform comprehensive analysis of overheads caused by data propagation through multi-hop distributed networks. We validate DCM through both simulations and experiments using MICAz motes. Similarity of the results from energy consumption analysis with both simulations and experimentations shows that DCM is realistic, compared to other models in terms of accuracy and diversity of the environments.

In this paper, we proposed that an area- and speed-effective fixed-point pipelined divider be used for reducing the bit-width of a division unit to fit a mobile rendering processor. To decide the bit-width of a division unit, error analysis has been carried out in various ways. As a result, when the original bit-width was 31-bit, the proposed method reduced the bit-width to 24-bit and reduced the area by 42% with a maximum error of 0.00001%.

In this paper, we apply a mutation operation based on a multivariate Cauchy distribution to fast evolutionary programming and analyze its effect in terms of various function optimizations. The conventional fast evolutionary programming in-cooperates the univariate Cauchy mutation in order to overcome the slow convergence rate of the canonical Gaussian mutation. For a mutation of n variables, while the conventional method utilizes n independent random variables from a univariate Cauchy distribution, the proposed method adopts n mutually dependent random variables that satisfy a multivariate Cauchy distribution. The multivariate Cauchy distribution naturally has higher probabilities of generating random variables in inter-variable regions than the univariate Cauchy distribution due to the mutual dependence among variables. This implies that the multivariate Cauchy random variable enhances the search capability especially for a large number of correlated variables, and, as a result, is more appropriate for optimization schemes characterized by interdependence among variables. In this sense, the proposed mutation possesses the advantage of both the univariate Cauchy and Gaussian mutations. The proposed mutation is tested against various types of real-valued function optimizations. We empirically find that the proposed mutation outperformed the conventional Cauchy and Gaussian mutations in the optimization of functions having correlations among variables, whereas the conventional mutations showed better performance in functions of uncorrelated variables.

The involvement of IEEE 802.15.4 Wireless Sensor Networks (WSNs) in diverse applications has made the realistic analysis of sensor power dissipation in distributed network environments an essential research issue. In this paper, we propose and thoroughly analyze a power dissipation model for Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) based IEEE 802.15.4 distributed multi-hop WSNs. Our model takes the loss rate of frames, neighbor sensors density in communication range of a sensor, number of hops, distance of source to the sink, and density of the network into account. We evaluate the impact of these factors on overall power dissipation. We also perform comprehensive analysis of overheads caused by message routing through multi-hop distributed networks. We validate our proposed model through Monte Carlo simulations. Results show that our power dissipation model is more realistic compared to other proposed models in terms of accuracy and multiplicity of the environments.

A new indexing technique for rapid evaluation of nested query on composite object is propoced, reducing the overall cost for retrieval and update. An extended B+ tree is introduced in which object identifier (OID) to be searched and path information usud for update of index record are stored in leaf node and subleaf node, respectively. In this method, the retrieval oeration is applied only for OIDs in the leaf node. The index records of both leaf and subleaf nodes are updated in such a way that the path information in the subleaf node and OIDs in the leaf node are reorganized by deleting and inserting the OIDs. The techniaue presented offers advantages over currently related indexing techniques in data reorganization and index allocation. In the proposed index record, the OIDs to be reorganized are always consecutively provided, and thus only the record directory is updated when an entire page should be removed. In addition, the proposed index can be allocate to a path with the length greater than 3 without splitting the path. Comparisons under a variety of conditions are given with current indexing techniques, showing improved performance in cost, i.e., the total number of pages accessed for retrieval and update.

Compared to multi-level signature file techniques, PSF (Partitioned Signature File) technique has less processing overhead by its characteristics of a simple file organization. In a multi-processor environment, the PSF technique also has an advantage that queries can be processed in parallel effectively by allocating one or more partitions to each processor. Main point of the PSF technique is a partitioning scheme based on a key selection. In this paper, an n-BFK (n-Bounded Floating Key) partitioning scheme is proposed, in which the number of segments for a key selection is bounded by n. The cost model is developed for the performance evaluation of the proposed scheme. By performance comparison with the existing schemes, the efficiencies of the proposed scheme are shown with respect to a disk access cost, a signature reduction ratio, and an uniformity of workload.