Hyunbum Kim

Maximum lifetime of reinforced barrier-coverage in Wireless Sensor Networks

A subset of sensors in wireless sensor networks provides barrier-coverage over an area of interest if the sensor nodes are dividing the area into two regions such that any object moving from one region to another is guaranteed to be detected by a sensor. In many practical scenarios, it may be desirable to detect an intruder that enters the region through any of its sides and exits through any other of its sides. That is, not only detect top-down movement, but also side-to-side, and even turn from one side to another. In this paper, we introduce a new barrier-coverage problem whose objective is to maximize the network lifetime such that any penetration of the intruder is detected. To solve the problem, we create a new form of sensor barriers, which we refer to as reinforced barriers, which can detect any movement variation of the attacker. Also, we propose three approaches to obtain these barriers from a given layout of sensor nodes, and we then compare their relative performances through extensive simulations.

Event-driven partial barriers in wireless sensor networks

Recently a barrier-coverage in wireless sensor networks (WSN), which detects a moving object from one side to another opposite side, has attracted lots of attention. Although it is highly desirable to consider a barrier-coverage which can detect any moving objects for multiple sides simultaneously in event-driven environment, an existing barrier does not support those properties. In this paper, we introduce a new type of barrier, event-driven partial barrier, which can detect or monitor every movement of mobile objects on paths among multiple hubs in event-driven environment. Based on the new barrier concept, we define k-EP barriers that a motion by mobile objects is guaranteed to be detected by at least k sensors. Also, we formally define a problem whose objective is to minimize the number of sensors in order to construct k-EP barriers for every hub. To solve the problem, we propose two novel approaches to maximize a network lifetime by minimizing the number of sensors with satisfying requirements of k-EP barriers. Then, we evaluate their relative performances through extensive simulations.

Optimal transmission range and actor movement in wireless sensor and Actor networks

We consider the design of wireless sensor and actor networks. Sensors are network nodes with a fixed location and limited transmission power. Actors are mobile nodes that may relocate their position to provide coverage to the sensor nodes. We consider the problem of relocating K actors from initial random locations to locations where every sensor node is able to communicate directly with at least one actor node. The new actor locations are chosen to minimize the transmission power that is necessary for the sensor nodes. Also, the pairing of actors to their new locations is such that the cost of relocating the actors is minimized.

On resilient event-driven partial barriers in mobile sensor networks

A barrier-coverage in wireless sensor networks (WSN), which is able to detect a mobile object from one side to another opposite side, is a critical problem for lots of applications. Because it is highly appropriate to consider a barrier-coverage in event-driven environment, Kim et al. recently introduced k-event-driven partial barriers (k-EP barriers) with static sensor nodes, which at least k sensors can detect or monitor every movement of mobile objects on paths among multiple hubs in event-driven environment. But, in case of failures of sensors, k-EP barriers should be recovered from those failures. In this paper, we introduce resilient event-driven partial barriers with mobile sensors, which can maintain k-EP barriers continuously as well as can recover from a failed status when there exist failed sensors on initially constructed k-EP barriers due to energy depletion of those sensors. Also, we formally define a problem whose objective is to minimize total moving distance of mobile sensors such that k-EP are maintained continuously by considering movements of mobile sensors. To solve the problem, we propose a novel approach to minimize total movement distance of mobile sensors to form k-EP barriers continuously. Then, we address future issues and directions for resilient event-driven partial barriers.

Optimization algorithms for transmission range and actor movement in wireless sensor and actor networks

Wireless sensor and actor networks are composed of static sensors and mobile actors. We assume actors have a random initial location in the two-dimensional sensing area. The objective is to move each actor to a location such that every sensor node is within a bounded number of hops from some actor. Because sensors have limited energy, the new actor locations are chosen to minimize the transmission range of the sensors. However, actors also have a limited (although larger) power supply, and their movement depletes their resources. It follows that by carefully choosing the new actor locations, the total actor movement can be minimized. In this paper, we introduce the problem of simultaneously minimizing the required transmission range and amount of actor movement. To find a solution, we formulate the problem using an ILP framework. For the ILP solution to be feasible, we introduce a finite set of possible actor locations such that an optimal solution is guaranteed to be found within this set. We also present a heuristic for this problem. As a preliminary step, we study minimizing the transmission range necessary for multi-hop communication. Various heuristics for this smaller problem are proposed and their results are compared by simulation. The best of these heuristics is then enhanced to incorporate minimizing the movement of actors, and its performance is compared to the optimal ILP solution.

Simultaneous optimization of transmission range and actor movement in WSANs

Wireless sensor and actor networks (WSANs) are composed of static sensor nodes and movable actors. We assume actors have a random initial location in the field. The objective is to move each actor to a location such that every sensor node is within one transmission hop from some actor. Because sensor nodes have limited energy, finding actor locations that minimize the transmission range required from the sensor nodes may significantly increase network lifetime. However, actors also have a limited (although larger) power supply, and their movement depletes their resources. It follows that an optimal pairing of actors with the chosen new locations may also provide energy savings for the actors. In this paper, we address the problem that simultaneously minimizes sensor transmission radius and total actor movement. Due to its complexity, we present a heuristic and compare it against an optimial ILP solution. More importantly, we consider two approaches for both the heuristic and the ILP. First, actor locations that minimize transmission range are found, and then the assignment of actors to locations is performed (double-step approach). Second, a joint-optimization (single-step) approach is proposed in which transmission range and actor movement are considered simultaneously. We show that the single-step approach outperforms the double-step approach.

Optimal transmission range for multi-hop communication in wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) consist of fixed sensor nodes and mobile actor nodes. Data is generated at the sensor nodes, and collected at the more powerful actor nodes. We consider the problem of finding the location for K actor nodes such that every sensor node is within d-hop from an actor node, where K and d are parameters of the problem. Our approach distinguishes itself in obtaining the minimum transmission radius necessary for such coverage to be possible. We provide an exact solution by via an integer-linear-programming formulation (ILP), and evaluate two heuristic approaches.

On secure data sharing in cloud environment

Over years, cloud computing has been rapidly changing the shape of modern computing environment. The problem of how to keep the confidentiality of user data against malicious entities including a cloud service provider has been recognized as a significant issue. This problem becomes even more complicated if a data is shared among multiple users. Recently, the idea of proxy re-encryption has been introduced to support secure data sharing among group members in cloud environment. However, in this scheme, a malicious user can collude with the server to decrypt unauthorized messages. The conditional proxy re-encryption (CPRE) aims to fix this problem by introducing a condition value into message encryption process and re-encryption key generation. We observe that CPRE becomes significantly inefficient when the membership of the group changes very actively and the size of the group is large since a new condition value is selected and re-encryption keys have to be generated for each user whenever the group membership is changed. This paper introduces a new CPRE in which the condition value is not associated with re-encryption keys. Whenever a group membership is changed, only a new condition value is distributed to the users via cloud server. As a result, the overhead of each user becomes significantly reduced at each membership change.

Pattern-Identified Online Task Scheduling in Multitier Edge Computing for Industrial IoT Services

In smart manufacturing, production machinery and auxiliary devices, referred to as industrial Internet of things (IIoT), are connected to a unified networking infrastructure for management and command deliveries in a precise production process. However, providing autonomous, reliable, and real-time offloaded services for such a production is an open challenge since these IIoT devices are assumed lightweight embedded platforms with limited computing performance. In this paper, we propose a pattern-identified online task scheduling (PIOTS) mechanism for the networking infrastructure, where multitier edge computing is provided, in order to handle the offloaded tasks in real time. First, historical IIoT task patterns in every timeslot are used to train a self-organizing map (SOM), which represents the features of the task patterns within defined dimensions. Consequently, offline task scheduling among edge computing-enabled entities is performed on the set of all SOM neurons using the Hungarian method to determine the expected optimal task assignments. In real-time context, whenever a task arrives at the infrastructure, the expected optimal assignment for the task is scheduled to the appropriate edge computing-enabled entity. Numerical simulation results show that the proposed PIOTS mechanism overcomes existing solutions in terms of computation performance and service capability.

Collision-free reinforced barriers in UAV networks

Abstract Unmanned Aerial Vehicle (UAV) networks have gained a lot of interest because of their effectiveness and great potential. One of major challenges in UAV networks is a collision avoidance and should be addressed carefully. Also, a barrier-coverage has been studied widely since it can be utilized in promising applications for border surveillance and intrusion detection. In this study, we introduce a framework for constructing a collision-free UAV reinforced barrier, which provides a guaranteed detection for various penetration types by intruders. Formally, we define a problem whose goal is to minimize total movement distance of UAVs such that a collision-free reinforced barrier is constructed from initial locations of UAVs. To solve the problem, we create potential positions which can support flexible movements of UAVs. Then, a zone-based novel approach is proposed. Furthermore, we evaluate the performance of the proposed scheme through extensive simulations.