Wireless sensor networks (WSNs) play a crucial role in Internet-of-Things (IoT) systems serving a variety of applications. They gather data from specific sensor nodes and transmit it to remote units for processing. When multiple applications share a WSN infrastructure, efficient scheduling becomes vital. In our research, we address the problem of application scheduling in WSNs. Specifically, we focus on scenarios where applications request data from monitoring points within the coverage area of a WSN. We propose a shared-data approach that reduces the network’s sensing and communication load by allowing multiple applications to use the same sensing data. To tackle the scheduling challenge, we introduce a genetic algorithm named GABAS and three greedy algorithms: LMPF, LMSF, and LTSF. These algorithms determine the order in which applications are admitted to the WSN infrastructure, considering various criteria. To assess the performance of our algorithms, we conducted extensive simulation experiments and compared them with standard scheduling methods. We also evaluated the performance of GABAS as compared to another genetic scheduling algorithm that has recently appeared in the literature. The overall experimental results show that the methods we propose outperform the compared approaches across various metrics, namely makespan, turnaround time, waiting time, and successful execution rate. In particular, our genetic algorithm proves to be highly effective in scheduling applications and optimizing the mentioned metrics.

With the advent of cloud computing , computation has become a commodity used by customers to access computing resources with no up-front investment, but as an on-demand and pay-as-you-go basis. Cloud providers make their infrastructure available to public so that anyone can obtain a virtual machine (VM) instance that can be remotely configured and managed. The cloud infrastructure is a large resource pool, allocated to VM instances on demand. In a multi-resource heterogeneous cloud, allocation state of the data center needs to be captured in metrics that can be used by allocation algorithms to make proper assignments of virtual machines to servers. In this paper, we propose two novel metrics reflecting the current state of VM allocation. These metrics can be used by online and offline VM placement algorithms in judging which placement would be better. We also propose multi-dimensional resource allocation heuristic algorithms showing how metrics can be used. We studied the performance of proposed methods and compared them with the methods from the literature. Results show that our metrics perform significantly better than the others and can be used to efficiently place virtual machines with high success rate.

Machine-to-machine communication (M2M) technology enables large-scale device communication and networking, including home devices and appliances. A critical issue for home M2M networks is how to efficiently integrate existing home consumer devices and appliances into an IP-based wireless M2M network with least modifications. Due to its popularity and widespread use in closed spaces, Wi-Fi is a good alternative as a wireless technology to enable M2M networking for home devices. This paper addresses the energy-efficient integration of home appliances into a Wi-Fi- and IP-based home M2M network. Toward this goal, we first propose an integration architecture that requires least modifications to existing components. Then, we propose a novel long-term sleep scheduling algorithm to be applied with the existing 802.11 power save mode. The proposed scheme utilizes the multicast DNS protocol to maintain device and service availability when devices go into deep sleep mode. We prototyped our proposed architecture and algorithm to build a M2M network testbed of home appliances. We performed various experiments on this testbed to evaluate the operation and energy savings of our proposal. We also did simulation experiments for larger scale scenarios. As a result of our test-bed and simulation experiments, we observed significant energy savings compared to alternatives while also ensuring device and service availability.

Abstract Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.

Graph stores are becoming increasingly popular among NOSQL applications seeking flexibility and heterogeneity in managing linked data. Conceptually and in practice, applications ranging from social networks, knowledge representations to Internet of things benefit from graph data stores built on a combination of relational and non-relational technologies aimed at desired performance characteristics. The most common data access pattern in querying graph stores is to traverse from a node to its neighboring nodes. This paper studies the impact of such traversal pattern to common data caching policies in a partitioned data environment where a big graph is distributed across servers in a cluster. We propose and evaluate a new graph aware caching policy designed to keep and evict nodes, edges and their metadata optimized for query traversal pattern. The algorithm distinguishes the topology of the graph as well as the latency of access to the graph nodes and neighbors. We implemented graph aware caching on a distributed data store Apache HBase in the Hadoop family. Performance evaluations showed up to 15x speedup on the benchmark datasets preferring our new graph aware policy over non-aware policies. We also show how to improve the performance of existing caching algorithms for distributed graphs by exploiting the topology information.

This paper introduces a distributed fault-tolerant topology control algorithm, called the Disjoint Path Vector (DPV), for heterogeneous wireless sensor networks composed of a large number of sensor nodes with limited energy and computing capability and several supernodes with unlimited energy resources. The DPV algorithm addresses the k-degree Anycast Topology Control problem where the main objective is to assign each sensor's transmission range such that each has at least k-vertex-disjoint paths to supernodes and the total power consumption is minimum. The resulting topologies are tolerant to k-1 node failures in the worst case. We prove the correctness of our approach by showing that topologies generated by DPV are guaranteed to satisfy k-vertex supernode connectivity. Our simulations show that the DPV algorithm achieves up to 4-fold reduction in total transmission power required in the network and 2-fold reduction in maximum transmission power required in a node compared to existing solutions.

In graph theory, k-core is a key metric used to identify subgraphs of high cohesion, also known as the `dense' regions of a graph. As the real world graphs such as social network graphs grow in size, the contents get richer and the topologies change dynamically, we are challenged not only to materialize k-core subgraphs for one time but also to maintain them in order to keep up with continuous updates. Adding to the challenge is that real world data sets are outgrowing the capacity of a single server and its main memory. These challenges inspired us to propose a new set of distributed algorithms for k-core view construction and maintenance on a horizontally scaling storage and computing platform. Our algorithms execute against the partitioned graph data in parallel and take advantage of k-core properties to aggressively prune unnecessary computation. Experimental evaluation results demonstrated orders of magnitude speedup and advantages of maintaining k-core incrementally and in batch windows over complete reconstruction. Our algorithms thus enable practitioners to create and maintain many k-core views on different topics in rich social network content simultaneously.

Supporting real-time and quality-of-service (QoS) traffic in multi-hop wireless mobile networks is challenging due to the high level of dynamism involved. In this paper, we propose a network layer solution in the form of a hybrid routing protocol to enable QoS traffic support in this class of networks. Our proposed protocol combines link state topology updates, source routing and on demand link cost dissemination to concurrently support multiple classes of QoS and normal flows. Our protocol provides for QoS traffic by intelligent path selection at the source nodes based on the required QoS parameters/levels and dynamically adapting the paths as network topology and conditions change. This solution does not require any other layers/components in the network stack to be QoS-aware and is therefore readily deployable over existing networks. We present experimental results from a simulation study on the performance of our protocol. Our results show that the proposed solution can provide efficient QoS traffic support in small-to-medium sized mobile networks, where up to 90% improvement in QoS metrics are observed in certain experiments.

We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for sensor networks, which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies, such as LMST and RNG, that can approximate minimum spanning tree and can be efficiently computed using only position or distance information of one-hop neighbors. The actual routing tree is constructed over these topologies. We also consider different parent selection strategies while constructing a routing tree. We compare each topology and parent selection strategy and conclude that the best among them is the shortest path strategy over LMST structure. Our solution also involves route maintenance procedures that will be executed when a sensor node fails or a new node is added to the network. The proposed solution is also adapted to consider the remaining power levels of nodes in order to increase the network lifetime. Our simulation results show that by using our power-aware localized approach, we can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here.

In this paper, we present OA-TDMA (OLSR-Aware TDMA), a TDMA based cross-layer channel access scheduling scheme which uses the information collected by the OLSR routing protocol. In OA-TDMA, each node makes decisions in a distributed manner with no central control, using the local information disseminated by the OLSR protocol. The distinctive feature of the OA-TDMA protocol lies in its weighting scheme where OA-TDMA approximates the traffic passing through each node by using the local topology information collected by OLSR. Our simulations on ns-2 confirm the significant performance improvement achieved by the combination of OLSR and OA- TDMA over other scheduling schemes considered in this paper.

In this paper we propose a distributed, self organizing, robust and energy efficient data gathering algorithm for sensor networks operating in environments where all the sensor nodes are not in direct communication range of each other and data aggregation is used while routing. Proposed algorithm is based on local minimum spanning tree (LMST) structure, which nodes can construct from the position of their 1-hop neighbors. Reporting tree is constructed from the sink by allowing only edges of LMST to join the tree, plus possibly some direct links to the sink. Each node selects as parent the LMST neighbor so that the total energy cost of route to the sink is minimal. We also describe route maintenance protocols to respond to predicted sensor failures and addition of new sensors. Our simulation results show that our algorithm prolongs the network lifetime significantly compared to some alternative schemes.

Bluetooth networks can be constructed as piconets or scatternets depending on the number of nodes in the network, Although piconet construction is a well-defined process specified in Bluetooth standards, scatternet formation policies and algorithms are not well specified. Among many solution proposals for this problem, only a few of them focus on efficient usage of bandwidth in the resulting scatternets. In this paper, we propose a distributed algorithm for the scatternet formation problem that dynamically constructs and maintains a scatternet based on estimated traffic flow rates between nodes. The algorithm is adaptive to changes and maintains a constructed scatternet for bandwidth-efficiency when nodes come and go or when traffic flow rates change. Based on simulations, the paper also presents the improvements in bandwidth-efficiency and reduction in energy consumption provided by the proposed algorithm

Bluetooth networks can be constructed as piconets or scatternets depending on the number of nodes in the network. Although piconet construction is a well-defined process specified in Bluetooth standards, scatternet construction policies and algorithms are not well specified. Among many solution proposals for this problem, only a few of them focus on efficient usage of bandwidth in the resulting scatternets. In this paper, we propose a distributed algorithm for the scatternet construction problem, that dynamically constructs and maintains a scatternet based on estimated traffic flow rates between nodes. The algorithm is adaptive to changes and maintains a constructed scatternet for bandwidth-efficiency when nodes come and go or when traffic flow rates change. Based on simulations, the paper also presents the improvements in bandwidth-efficiency provided by the proposed algorithm.

We propose a distributed and measurement-based method to reduce the degree of free riding in P2P networks. We primarily focus on developing schemes to locate free riders and on determining policies that can be used to take actions against them. Our proposed schemes require each peer to monitor its neighboring peers, make decisions if they exhibit any kind of free riding, and take appropriate actions if required.

Palmtop computers are rapidly becoming the popular platform of choice for running personal productivity applications, but their networking capabilities are still lagging behind user expectations.Due to memory size, cost, and power considerations most palmtop computers support only limited form of point-to-point communication, namely, connection via a PSTN modem or a serial RS-232 cable.Due to wired point-to-point nature of these interfaces, satisfactory solutions for multi-point communication and direct LAN connection do not yet exist..The BlueSky project aims at providing a low-cost, lowpower, indoor RF wireless networking solution for handheld devices.Our solution consists of two components; a BlueSky wireless attachment that plugs into the standard serial port of any palmtop device, and a LAN access point that acts as a layer 213 bridge between the wireless and the wired part of the network.Palmtop devices use dialup networking software and PPP to connect via BlueSky to the network.BlueSky enables MobileIP style seamless roaming between access points without requiring any changes to the communication stack of plamtop devices.Our roaming enhancements to PPP are implemented in the PPP server, the access point, and the BlueSky attachment, all of which are completely transparent to the palmtop device.In this paper, we present our design rationale and implementation experience of building the BlueSky system.We show in what ways low cost, low power, and form factor constraints affect the choice of protocols and function placement in wireless networking systems.We use PPP based mobility solution as an example to illustrate what design adjustments and compromises one has to make to build a working solution.Based on our experience, we recommend making a slight modification to the dialup networking stack of palmtop computers.Our proposed modification offers an efficient, lower cost, and lighter-weight wireless networking solution which is particularly attractive for enabling mobility over emerging short range, low power wireless technologies, such as IrDA, HomeRF and Bluetooth.Permission Lo make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the tirst page.To copy otherWe, to republish, to post on servers or to redistribute to lists.rcquircs prior specific permission and/or a fee.