Matthias R. Brust

Local positioning for environmental monitoring in wireless sensor and actor networks

Location estimation of sensor nodes is an essential part of most applications for wireless sensor and actor networks (WSAN). The ambiguous location information often makes the collected data useless in these applications. Environmental monitoring in particular, relies on an accurate position estimation in order to process or evaluate the collected data. In this paper, we present a novel and scalable approach for positioning of mobile sensor nodes with the goal of monitoring the Amazon river. The actors in the scenario are stationary and positioned at reachable spots on the land alongside the river whereas sensor nodes are thrown into the river to collect data such as water temperature, depth and geographical features. The actors are not equipped with positioning adaptors and they are only aware of their distances from the other actors. The sensor nodes collect data and forward it to the actors. While floating in the river, sensor nodes are often multiple hops away from the actor nodes, which makes it challenging to apply traditional positioning techniques. Through extensive simulations, we show that the positioning of the nodes is feasible using a multi-hop approach with local information exchange only.

WACA: A Hierarchical Weighted Clustering Algorithm Optimized for Mobile Hybrid Networks

Clustering techniques create hierarchal network structures, called clusters, on an otherwise flat network. In a dynamic environment-in terms of node mobility as well as in terms of steadily changing device parameters-the clusterhead election process has to be re-invoked according to a suitable update policy. Cluster re-organization causes additional message exchanges and computational complexity and it execution has to be optimized. Our investigations focus on the problem of minimizing clusterhead re-elections by considering stability criteria. These criteria are based on topological characteristics as well as on device parameters. This paper presents a weighted clustering algorithm optimized to avoid needless clusterhead re- elections for stable clusters in mobile ad-hoc networks. The proposed localized algorithm deals with mobility, but does not require geographical, speed or distances information.

Multimedia content distribution in hybrid wireless networks using weighted clustering

Fixed infrastructured networks naturally support centralized approaches for group management and information provisioning. Contrary to infrastructured networks, in multi-hop ad-hoc networks each node acts as a router as well as sender and receiver. Some applications, however, requires hierarchical arrangements that¿for practical reasons¿has to be done locally and self-organized. An additional challenge is to deal with mobility that causes permanent network partitioning and reorganizations. Technically, these problems can be tackled by providing additional uplinks to a backbone network, which can be used to access resources in the Internet as well as to inter-link multiple ad-hoc network partitions, creating a hybrid wireless network. In this paper, we present a prototypically implemented hybrid wireless network system optimized for multimedia content distribution. To efficiently manage the ad-hoc communicating devices a weighted clustering algorithm is introduced. The proposed localized algorithm deals with mobility, but does not require geographical information or distances

Dynamic multi-hop clustering for mobile hybrid wireless networks

In mobile wireless networks communication is often improved by sending messages along a stable backbone of more reliable communication paths. Building such a backbone requires efficient clustering algorithms which aggregate network nodes into logical groups, each group being managed by a clusterhead and any two neighboring clusters being interconnected by at least one gateway node or gateway path. In this concept k-hop clustering refers to cluster structures where cluster members are at most k hops away from their clusterhead. While the dynamicity of mobile wireless network is often considered as a challenge, in this work we explicitly exploit node mobility in order to support cluster formation and maintenance of k-hop clusters. The described KHOPCA algorithm consists of a set of easy to implement rules which form and maintain k-hop sized clusters in a purely localized way. In a static network cluster formation is limited to a constant number of messages exchanges among neighboring nodes. In dynamic networks the localized nature of the described rules promise a fast cluster convergence and low communication complexity in case of mobility triggered cluster reconfiguration.

Topology-based Clusterhead Candidate Selection in Wireless Ad-hoc and Sensor Networks

Clustering techniques create hierarchal network structures, called clusters, on an otherwise flat network. Neighboring devices elect one appropriate device as clusterhead. Due to the dynamic environment, clusterhead selection becomes an important issue. We consider the problem of appropriate clusterhead selection in wireless ad-hoc networks and sensor networks. This work presents topological criteria for robust clusterhead candidate selection, resilient to sporadic node mobility and failure as well as for efficient information dissemination. One of the main ideas of our approach is to avoid selecting nodes located close to the network partition border as such nodes are more likely to move out of the partition, thus causing a clusterhead re-election. We conducted experiments both for static topologies as well as for cases in the presence of node mobility. Our results showed that the frequency of clusterhead re-election and average shortest path length from the clusterhead decrease when considering topological criteria. Additionally, the clusters tend to be robust to clusterhead failure. The presented mechanisms rely on local topological information only and do not require geographical data.

Multi-hop localization system for environmental monitoring in wireless sensor and actor networks

Location estimation of sensor nodes is an essential part of most applications for wireless sensor and actor networks. The ambiguous location information often makes the collected data useless in these applications. Environmental monitoring relies on an accurate position estimation to process or evaluate the collected data. In this paper, we present a novel and scalable approach for positioning of mobile sensor nodes with the goal of monitoring the Amazon river. The actors in the scenario are stationary and positioned at reachable spots on the land alongside the river whereas sensor nodes are thrown into the river to collect data such as water temperature, depth, and geographical features. The actors are not equipped with positioning adaptors, and they are only aware of their distances from the other actors. The sensor nodes collect data and forward it to the actors. While floating in the river, sensor nodes are often multiple hops away from the actors, which makes it challenging to apply traditional positioning techniques. Through extensive simulations, we show that the nodes can be efficiently positioned using a multi‐hop approach with local information exchange only. The introduced approach is also applied to a scenario, where monkey swarm monitoring is simulated, to test the generalizability of the algorithm. Copyright

Connectivity Stability in Autonomous Multi-level UAV Swarms for Wide Area Monitoring

Many different types of unmanned aerial vehicles (UAVs) have been developed to address a variety of applications ranging from searching and mapping to surveillance. However, for complex wide-area surveillance scenarios, where fleets of autonomous UAVs must be deployed to work collectively on a common goal, multiple types of UAVs should be incorporated forming a heterogeneous UAV system. Indeed, the interconnection of two levels of UAVs---one with high altitude fixed-wing UAVs and one with low altitude rotary-wing UAVs---can provide applicability for scenarios which cannot be addressed by either UAV type. This work considers a bi-level flying ad hoc networks (FANETs), in which each UAV is equipped with ad hoc communication capabilities, in which the higher level fixed-wing swarm serves mainly as a communication bridge for the lower level UAV fleets, which conduct precise information sensing. The interconnection of multiple UAV types poses a significant challenge, since each UAV level moves according to its own mobility pattern, which is constrained by the UAV physical properties. Another important challenge is to form network clusters at the lower level, whereby the intra-level links must provide a certain degree of stability to allow a reliable communication within the UAV system. This article proposes a novel mobility model for the low-level UAVs that combines a pheromone-based model with a multi-hop clustering algorithm. The pheromones permit to focus on the least explored areas with the goal to optimize the coverage while the multi-hop clustering algorithm aims at keeping a stable and connected network. The proposed model works online and is fully distributed. The connection stability is evaluated against different measurements such as stability coefficient and volatility. The performance of the proposed model is compared to other state-of-the-art contributions using simulations. Experimental results demonstrate the ability of the proposed mobility model to significantly improve the network stability while having a limited impact on the wide-area coverage.

Hycast- podcast discovery in mobile networks

Podcasts are a popular way to provide multimedia information about certain topics. A multitude of podcast servers exist in the Internet, allowing people to subscribe to them. Typically, podcasts are downloaded onto desktop computers and copied on mobile devices to be played while being on the move. In this paper, we extend the idea of podcasts, making them available in mobile network environments. In particular, HyCast does not rely on central podcast directories. Instead, HyCast also allows discovering, subscribing to, and downloading podcasts and episodes in the local neighborhood. For the dissemination of podcast information, we introduce and evaluate two different strategies. One is based on peer-to-peer communication between one-hop neighbors. The second one employs clustering to reduce the overhead of the podcast information dissemination.

SOFROP: Self-organizing and fair routing protocol for wireless networks with mobile sensors and stationary actors

Wireless sensor and actor networks (WSAN) have become increasingly popular in recent years. The combined operation between sensor nodes and actors results in a major advantage compared to pure sensor networks extending the range of possible applications. One of the emerging applications is the Amazon scenario in which stationary actors are deployed at accessible points in a thick forest structure and sensor nodes are thrown in a river flowing through the forest to gather observations from unreachable areas. This unprecedented and unique setting exposes two important challenges: (a) the dynamics of the river forms a continuously varying topology of sensor nodes requiring a highly adaptive network organization and (b) the inherent features of sensor and actor nodes, combined with rapid changes in the link structure of the network requiring efficient bandwidth utilization and data transmission. In this paper, we address these challenges by introducing SOFROP, a self-organizing and fair routing protocol for WSANs. Through extensive simulations, we point out two highlights of SOFROP: the efficient lightweight routing that is optimized for fairness and the locally acting adaptive overlay network formation.

Inquiring the Potential of Evoking Small-World Properties for Self- Organizing Communication Networks

Mobile multi-hop ad hoc networks allow establishing local groups of communicating devices in a self-organizing way. However, in a global setting such networks fail to work properly due to network partitioning. Providing that devices are capable of communicating both locally-e.g. using Wi-Fi or Bluetooth-and additionally also with arbitrary remote devices-e.g. using GSM/UMTS links-the objective is to find efficient ways of inter-linking multiple network partitions. Tackling this problem of topology control, we focus on the class of small-world networks that obey two distinguishing characteristics: they have a strong local clustering while still retaining a small average distance between two nodes. This paper reports on results gained investigating the question if small-world properties are indicative for an efficient link management in multiple multi-hop ad hoc network partitions.