With the increase of IoT devices, P2P-based IoT platforms have been attracting attention because of their capabilities of building and maintaining their networks autonomously in a decentralized way. In particular, Skip Graph, which has a low network rebuilding cost and allows range search, is suitable for the platform. However, when data observed at geographically close points have similar values (i.e. when data have strong spatial autocorrelation), existing types of Skip Graph degrade their search performances. In this paper, we propose a query transfer method that enables efficient search even for spatially autocorrelated data by adaptively using two-types of Skip Graph depending on the key-distance to the target key. Simulation results demonstrate that the proposed method can reduce the query transfer distance compared to the existing method even for spatially autocorrelated data.

An overview of the evolution of intelligent transport systems (ITS) supported by advances in information and communication technologies is presented. Focusing on a sensing platform as one of the ITS applications, this paper presents a survey on vehicular ad hoc network-based geographic routing. In addition to the minimum requirement of street-awareness based on street maps, traffic and packet-awareness are considered essential to achieve acceptable packet delivery performance. In particular, in addition to statistical information, real-time traffic and packet level information are indispensable for making routing protocols feasible and effective. Considering traffic conditions that are highly space- and time-dependent, static nodes can be used to assist with geographic routing, and a protocol workable under a partial deployment of static nodes is considered.

Much work in cooperative communication has been done from the perspective of the physical and network layers. However, the exact impact of signal error rate performance on cooperative routing discovery still remains unclear in multihop ad hoc networks. In this paper, we show the symbol error rate (SER) performance improvement obtained from cooperative commutation, and examine how to incorporate the factor of SER into the distributed routing discovery scheme called DGCR (Dynamic Geographic Cooperative Routing). For a single cooperative communication hop, we present two types of metric to specify the degree that one node is suitable for becoming the relay node. One metric is the potential of a node to relay with optimal SER performance. The other metric is the distance of a node to the straight line that passes through the last forwarding node and the destination. Based on location knowledge and contention scheme, we combine the two metrics into a composite metric to choose the relay node. The forwarding node is chosen dynamically according to the positions of the actual relay node and the destination. Simulation results show that our approach outperforms non-cooperative geographic routing significantly in terms of symbol error rate, and that DGCR's SER performance is better than traditional geographic cooperative routing with slight path length increase.

In classical routing protocols, geographical distances/locations are typically used as the metric to select the best route, under the assumption that shorter distances exhibit lower energy consumption and nodes within the communication range of the sender can receive packets with a certain success probability. However, in underwater acoustic sensor networks (UASNs), sound propagation in the ocean medium is more complex than that in the air due to many factors, including sound speed variations and the interaction of sound waves with the sea surface and floor, causing the sound rays to bend. Therefore, propagation of sound is anisotropic in water, and may cause a phenomenon called shadow zone where nodes in the communication range of the sender cannot hear any signal. This renders conventional routing protocols no longer energy-efficient. In this paper, we make use of the ray-model to account for the environment-dependent behavior of the underwater channel, re-define nodes' one-hop neighbors based on signal attenuation rather than geographical distance, and design a distributed energy-efficient routing protocol for UASNs. Results show that our ray-model-based routing policy consistently outperforms the shortest path policy, and performs very close to the optimal one in several scenarios.

In this paper, we propose a geographic location-based distributed routing (GDR) system. The GDR system provides information lookup based on latitude and longitude coordinates. Each node of the GDR system utilizes the coordinates as an identifier (ID), and manages an overlay routing table. An ID is generated to reflect the geographical location without using Space Filling Curve (SFC). The ID is in cartesian format (x, y), which represents the longitude x and latitude y. In a system with N nodes, each node has a routing table of size log N and a search is possible in O(log N). We evaluate the routing performance of GDR and other systems based on Chord, Kademlia and CAN. We show that in both the ID is in cartesian format and the ID is generated by using SFC, GDR, Chord and Kademlia have the same mean and the same variance of the path length, while the mean and the variance of the relay length of GDR are smaller than those of Chord and Kademlia. Furthermore, while GDR and CAN have the same mean and the same variance of the relay length, the mean and the variance of the path length of GDR are smaller than those of CAN.

In this paper, we present Greedy Routing for Maximum Lifetime (GRMax) [1],[2] which can use the limited energy available to nodes in a Wireless Sensor Network (WSN) in order to delay the dropping of packets, thus extend the network lifetime. We define network lifetime as the time period until a source node starts to drop packets because it has no more paths to the destination [3]. We introduce the new concept of Network Connectivity Aiming (NCA) node. The primary goal of NCA nodes is to maintain network connectivity and avoid network partition. To evaluate GRMax, we compare its performance with Geographic and Energy Aware Routing (GEAR) [4], which is an energy efficient geographic routing protocol and Greedy Perimeter Stateless Routing (GPSR) [5], which is a milestone among geographic routing protocol. We evaluate and compare the performance of GPSR, GEAR, and GRMax using OPNET Modeler version 15. The results show that GRMax performs better than GEAR and GPSR with respect to the number of successfully delivered packets and the time period before the nodes begin to drop packets. Moreover, with GRMax, there are fewer dead nodes in the system and less energy is required to deliver packets to destination node (sink).

Geographic routing uses the geographical location information provided by nodes to make routing decisions. However, the nodes can not obtain accurate location information due to the effect of measurement error. A new routing strategy using maximum expected distance and angle (MEDA) algorithm is proposed to improve the performance and promote the successive transmission rate. We firstly introduce the expected distance and angle, and then we employ the principal component analysis to construct the object function for selecting the next hop node. We compare the proposed algorithm with maximum expectation within transmission range (MER) and greedy routing scheme (GRS) algorithms. Simulation results show that the proposed MEDA algorithm outperforms the MER and GRS algorithms with higher successive transmission rate.

In this paper, a Spectrum-Aware Routing (SAR) protocol for cognitive radio ad hoc networks, (CRAHN), is proposed which is robust to primary user activity and node failures. The protocol allows nodes to collect spectrum information during a spectrum management interval followed by a transmission period. Cognitive users discover routes by joint channel and next hop selection (synchronization) in the transmission intervals. A restricted geographical routing approach is adopted to avoid performance degradation specially due to routing overhead. We also add spectrum mobility capabilities to routes in our proposed method to provide robustness to primary user activity. SAR protocol performance is investigated through simulations of different scenarios and is compared with the most similar work, CAODV protocol. The results indicate that SAR can achieve significant reduction in control overhead as well as improved throughput.

To provide scalability against group size, Global Location Search based Hierarchical Geographic Multicast Protocols (GLS-HGMPs) have recently been proposed for wireless sensor networks. To reduce the communication overhead imposed by the global location search and prevent the multicast data detour imposed by the hierarchical geographic multicasting in GLS-HGMPs, this letter proposes Local Location Search based Progressive Geographic Multicast Protocol (LLS-PGMP). Simulation results show that LLS-PGMP is superior to GLS-HGMPs.

This paper proposes a method for reducing redundant greedy-perimeter transitions in beacon-less geographic routing for wireless sensor networks (WSNs). Our method can be added to existing routing methods. Using a bloom filter, each node can detect a routing loop, and then the node stores the information as “failure history”. In the next forwarding the node can avoid such bad neighbors based on the failure history. Simulation results demonstrate the benefit of our method.

Fractal structures emerge from statistical and hierarchical processes in urban development or network evolution. In a class of efficient and robust geographical networks, we derive the size distribution of layered areas, and estimate the fractal dimension by using the distribution without huge computations. This method can be applied to self-similar tilings based on a stochastic process.

Recently in ad hoc networks, routing schemes using location information which is provided by GPS (Global Position System) have been proposed. However, many routing schemes using location information assume that a source node has already known the location information of the destination node and they do not adapt to large ad hoc networks. On another front, the autonomous clustering scheme has been proposed to construct the hierarchical structure in ad hoc networks and adapt to large ad hoc networks. However, even when the hierarchical structure is introduced, there is some problem. The data delivery ratio becomes lower as the node speed becomes higher, and clusterheads have much overhead in the hierarchical routing scheme based on the autonomous clustering scheme. In order to cope with these problems, this paper proposes a new Hierarchical Geographical Routing with Alternative Paths (Hi-GRAP) using the autonomous clustering scheme and shows the effectiveness of the proposed hierarchical geographical routing in comparison with GPSR, Hi-AODV and AODV through simulation experiments with respect to the amount of control packets and the data delivery ratio.

In this letter, we propose a revised geographic routing protocol and a scheduling algorithm to support real-time applications, which are often observed in wireless sensor networks. In order to meet real-time requirement, a specific application is modeled as an (m,k)-firm stream that has a property of weakly hard real-time system. In addition, both a priority-based scheduling and a geographic forwarding scheme based on delay, distance, and remaining slack time are newly proposed. Simulations and their analysis are followed to validate the suitability of reduced dynamic failure probability and extended network lifetime.

In wireless sensor networks (WSNs), geographic routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Geographic routing with location errors may produce serious problems such as disconnected links and data transmission delays. In this letter, we present an efficient location error compensation algorithm for the geographic routing. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.

The IEEE 802.15.4a standard enables geographical routing in ZigBee networks but previous geographical routing algorithms can suffer high packet loss due to the interference effects. This letter proposes an interference-aware energy-efficient geographical routing algorithm for the IEEE 802.15.4a networks. The proposed algorithm estimates the energy cost by considering the interference effects and forwards a packet to the neighbor with the lowest energy cost to advance. Experimental results show that the proposed algorithm outperforms the previous algorithms in terms of the delivery ratio and the energy consumption.

This position paper outlines the author's view on architectural directions and key technology enablers for the future mobile Internet. It is pointed out that mobile and wireless services will dominate Internet usage in the near future, and it is therefore important to design next-generation network protocols with features suitable for efficiently serving emerging wireless scenarios and applications. Several key requirements for mobile/wireless scenarios are identified - these include new capabilities such as dynamic spectrum coordination, cross-layer support, disconnection tolerant routing, content addressing, and location awareness. Specific examples of enabling technologies which address some of these requirements are given from ongoing research projects at WINLAB. Topics covered briefly include wireless network virtualization, the cache-and-forward (CNF) protocol, geographic (GEO) protocol stack, cognitive radio protocols, and open networking testbeds.

Geographic routing for wireless sensor networks requires a source that can encapsulate the location of a sink in each data packet. How a source can obtain the location of a sink with low overhead is a difficult issue. This letter proposes a Quorum Based Sink Location Service (QSLS) which can be exploited by most geographic routing protocols in arbitrary irregular wireless sensor networks.

In Mobile Ad hoc Networks (MANET) geographic routing is characterized by local forwarding decision. Links with a long progress are preferred under the greedy forwarding rule. However in a real system long links tend to have a high packet loss rate due to multipath fading. A sub-optimal solution may separately exploit path diversity or rate adaptation. In this paper we study channel efficiency of multi-hop forwarding and try to jointly optimize rate adaptation and forwarder selection in geographic routing by the tradeoff between progress and instantaneous rate. We define a new metric -- Bit Transfer Speed (BTS) -- as the ratio of the progress made towards the destination to the equivalent time taken to transfer a payload bit. This metric takes overhead, rate and progress into account. Then we propose a packet forwarding scheme that Opportunistically exploits both long Progress and Adaptive Rate (OPAR) by a cross-layer design of routing and MAC. In OPAR each node selects for a packet the forwarder with the highest BTS. The forwarder changes as local topology (progress), packet size (overhead ratio) or channel state (data rate) varies. Simulation results show that compared with the normalized advance (NADV) [7] scheme and contention-based forwarding (CBF) [17] scheme, OPAR has lower packet loss and can effectively reduce channel occupation time by over 30% in the scenario with moderate mobility speeds.

Recently, in mobile ad hoc networks, routing schemes using location information have been proposed. Most of these schemes assume that the source node already knows the location information of the destination node. However, since all nodes are always moving, it is difficult to apply this assumption to the real mobile ad hoc environment. In order to cope this difficulty, this paper presents a new routing scheme HGR (a Hybrid Greedy Routing with location and velocity information), which considers the location and velocity information of the destination node and the neighboring nodes. In HGR, when a source node creates a route to a destination node, the future location of neighboring nodes and the destination node predicted by the source node is calculated using these location and velocity information. And the source node sends data packets to the neighboring node that is the closest to the destination node based on these predicted location and velocity information. This paper shows that HGR achieves high data delivery ratio and fewer overheads for the route creation and maintenance through simulation experiments.

Sensor networks that carry heterogeneous traffics and are responsible for reporting very time-critical important events necessitate an efficient and robust data dissemination framework. Designing such a framework, that can achieve both the reliability and delay guarantee while preserving the energy efficiency, namely multi-constrained QoS (MCQoS), is a challenging problem. Although there have been many research works on QoS routing for sensor networks, to the best of our knowledge, no one addresses the above three service parameters all together. In this paper, we propose a new aggregate routing model and a distributed aggregate routing algorithm (DARA) that implements the model for achieving MCQoS. DARA is designed for multi-sink, multipath and location aware network architecture. We develop probabilistic models for multipath reliability constraint, sojourn time of a packet at an intermediary node and node energy consumption. Delay-differentiated multi-speed packet forwarding and in-node packet scheduling mechanisms are also incorporated with DARA. The results of the simulations demonstrate that DARA effectively improves the reliability, delay guarantee and energy efficiency.