Mustafa Ilhan Akbas

APAWSAN: Actor positioning for aerial wireless sensor and actor networks

The node mobility is a natural element of many wireless sensor and actor network (WSAN) applications. Recent advances in the development of small unmanned aerial vehicles (UAVs) with built in sensors made it possible to deploy aerial sensor and actor networks. An aerial network composed of small UAVs enables high quality observation for events while reducing the number of personnel and the risk for the operators. In order to have an effective data collection, the positioning of actors plays a critical role in aerial WSANs. In this paper we propose an actor positioning strategy for aerial WSANs considering the scenario of toxic plume observation after a volcanic eruption, which is one of the emerging applications of aerial UAV networks. Measuring the composition of volcanic plumes allows the computation of volcanogenic fluxes and provides insights into volatile degassing mechanisms. The actors in the proposed approach use a lightweight and distributed algorithm to form a self organizing network around the central UAV, which has the role of the sink in the WSAN. Our algorithm makes use of the Valence Shell Electron Pair (VSEPR) theory of chemistry, which is based on the correlation between molecular geometry and the number of atoms in a molecule. The performance of the proposed practical positioning algorithm is presented through extensive simulations.

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.

A Mobility Model of Theme Park Visitors

Realistic human mobility modeling is critical for accurate performance evaluation of mobile wireless networks. Movements of visitors in theme parks affect the performance of systems which are designed for various purposes including urban sensing and crowd management. Previously proposed human mobility models are mostly generic while some of them focus on daily movements of people in urban areas. Theme parks, however, have unique characteristics in terms of very limited use of vehicles, crowds social behavior, and attractions. Human mobility is strongly tied to the locations of attractions and is synchronized with major entertainment events. Hence, realistic human mobility models must be developed with the specific scenario in mind. In this paper, we present a novel model for human mobility in theme parks. In our model, the nondeterminism of movement decisions of visitors is combined with deterministic behavior of attractions in a theme park. The attractions are categorized as rides, restaurants, and live shows. The time spent at these attractions are computed using queueing-theoretic models. The realism of the model is evaluated through extensive simulations and compared with the mobility models SLAW, RWP and the GPS traces of theme park visitors. The results show that our proposed model provides a better match to the real-world data compared to the existing models.

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

Social network generation and friend ranking based on mobile phone data

Social networking websites have been increasingly popular in the recent years. The users create and maintain their social networks by themselves in these websites by establishing or removing the connections to friends and sites of interests. The smart phones not only create a high availability for social network applications, but also serve for all forms of digital communication such as voice or video calls, e-mails and texts, which are also the ways to form or maintain our social network. In this paper, we deal with the problem of automatically generating and organizing social networks by analyzing and assessing mobile phone usage and interaction data. We assign weights to the different types of interactions. The interactions among users are then evaluated based on these weight values for certain periods of time. We use these values to rank the friends of users by a sports ranking algorithm, which recognizes the changes in the collected data over time.

Lightweight routing with dynamic interests in wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) have been increasingly popular for environmental monitoring applications in the last decade. While the deployment of sensor nodes enables a fine granularity of data collection, resource-rich actor nodes provide further evaluation of the information and reaction. Quality of service (QoS) and routing solutions for WSANs are challenging compared to traditional networks because of the limited node resources. WSANs also have different QoS requirements than wireless sensor networks (WSNs) since actors and sensor nodes have distinct resource constraints. In this paper, we present, LRP-QS, a lightweight routing protocol with dynamic interests and QoS support for WSANs. LRP-QS provides QoS by differentiating the rates among different types of interests with dynamic packet tagging at sensor nodes and per flow management at actor nodes. The interests, which define the types of events to observe, are distributed in the network. The weights of the interests are determined dynamically by using a nonsensitive ranking algorithm depending on the variation in the observed values of data collected in response to interests. Our simulation studies show that the proposed protocol provides a higher packet delivery ratio and a lower memory consumption than the existing state of the art protocols.

Modeling visitor movement in theme parks

Realistic modeling of the movement of people in an environment is critical for evaluating the performance of mobile wireless systems such as urban sensing or mobile sensor networks. Existing human movement models are either fully synthetic or rely on traces of actual human movement. There are many situations where we cannot perform an accurate simulation without taking into account what the people are actually doing. For instance, in theme parks, the movement of people is strongly tied to the locations of the attractions and is synchronized with major external events. For these situations, we need to develop scenario specific models. In this paper, we present a model of the movement of visitors in a theme park. The nondeterministic behavior of the human walking pattern is combined with the deterministic behavior of attractions in the theme park. The attractions are divided into groups of rides, restaurants and live shows. The time spent by visitors at different attractions is calculated using specialized queuing-theoretic models. We compare the realism of the model by comparing its simulations to the statistics of the theme parks and to real-world GPS traces of visitor movement. We found that our model provides a better match to the real-world data compared to current state-of-the-art movement models.

Lightweight Routing with QoS Support in Wireless Sensor and Actor Networks

Wireless sensor and actor networks (WSANs) can be used for monitoring physical environments and acting according to the observations. In order to differentiate the actions based on the sensed information, WSANs comprise of various applications with different quality of service (QoS) requirements. QoS solutions for WSANs are challenging compared to traditional networks because of the limited resource capabilities of sensor nodes. In terms of QoS requirements, WSANs also differ from WSNs since actors and sensors have distinct resource constraints. In this paper we present LRP-QS, lightweight routing protocol with QoS support for WSANs. Our protocol provides QoS by differentiating the rates among different types of applications with dynamic packet tagging at the sensor nodes and per flow management at the actor nodes. Through extensive simulations we observe a greater packet delivery ratio and a better memory consumption rate in comparison with the related mechanisms.

Localization for Wireless Sensor and Actor Networks with Meandering Mobility

Environmental monitoring applications for wireless sensor and actor networks rely on position estimation in order to process or evaluate the observed data. The absence of efficient positioning techniques for sensor nodes operating in harsh environments calls for novel approaches. While monitoring the Amazon river, unprecedented characteristics of the river and its surroundings challenge the node communications and drifting of the nodes makes it difficult to use the existing positioning methods. To address these challenges, we propose a multi-hop localization technique that takes advantage of sensor mobility with local information exchange. The collected information is used to enrich the environmental data with location information. The maximum hop distance for actor affiliation is also adapted according to network characteristics to improve energy consumption behavior. The motion of the sensor nodes follows the advection of the fluid parcels in the river, which is modeled as a combination of a central streamline with a meandering motion around the rough surface. This translates into a stretching topology with correlated motion for sensor nodes. Through extensive simulations, we show that the nodes can be efficiently positioned using the proposed approach, as our technique is compliant with the movement patterns of the sensor nodes in the realistic mobility model of the river.

Actor positioning based on molecular geometry in aerial sensor networks

Advances in unmanned aerial vehicle (UAV) technology and wireless sensor and actor networks (WSAN) made it possible to equip small UAVs with sensors and deploy aerial sensor and actor networks. Aerial sensor networks enable high quality observation of events while reducing the number of requirements. Positioning of UAVs with actor nodes is critical in these systems for effective data collection. In this paper we propose an actor positioning strategy for aerial WSANs considering the scenario of toxic plume observation after a volcanic eruption. The positioning algorithm utilizes the Valence Shell Electron Pair Repulsion (VSEPR) theory of chemistry, which is based on the correlation between molecular geometry and the number of atoms in a molecule. The limitations of the basic VSEPR theory are eliminated by extending the approach for multiple central data collectors. The simulations show that the proposed system provides high connectivity and coverage for the aerial sensor network.