• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.136-146
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• 2006

In Wireless Sensor Network(WSN) a sensor node transfers sensing data to the base-node through multi-hop because of the limited transmission range. Also because of the limited energy of the sensor node, the sensor nodes are required to consume their energy evenly to prolong the lifetime of the network. LMPR is a routing protocol for WSN, LMPR configures the network autonomously based on level which is the depth from the base-node, and distributes the transmission and computation load of the network to each sensor node. This paper implements LMPR on TinyOS and experiments on the performance of LMPR in WSN. As the result, the average of the received rate of LMPR is 91.39% and LMPR distributes the load of the transmission and computation about 4.6 times compare to the shortest cost routing protocol. We expect LMPR evenly distributes the transmission and computation load of the network to each node, and the lifetime of the network will be longer than it used to be.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.95-105
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• 2023

To make the network energy efficient and to protect the network from malignant user's energy efficient grid based secret key sharing scheme is proposed. The cost function is evaluated to select the optimal nodes for carrying out the data transaction process. The network is split into equal number of grids and each grid is placed with certain number of nodes. The node cost function is estimated for all the nodes present in the network. Once the optimal energy proficient nodes are selected then the data transaction process is carried out in a secured way using malicious nodes filtration process. Therefore, the message is transmitted in a secret sharing method to the end user and this process makes the network more efficient. The proposed work is evaluated in network simulated and the performance of the work are analysed in terms of energy, delay, packet delivery ratio, and false detection ratio. From the result, we observed that the work outperforms the other works and achieves better energy and reduced packet rate.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.41-51
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• 2009

Recently, there are many researches on security to remove vulnerability which is caused by wireless communication in wireless sensor networks. To guarantee secure communication, we should basically provide key management for each node, mutual authentication and key agreement protocol between two nodes. Although many protocols are presented to supply these security services, some of them require plentiful storage memory, powerful computation and communication capacity. In this paper, we propose a lightweight and efficient authentication and key agreement protocol between two sensor nodes, which is an enhanced version of Juang's scheme. In Juang's protocol, sensor node's information used to share a secret key should be transmitted to registration center via a base station. On the contrary, since node's information in our protocol is transmitted up to only base station, the proposed scheme can decrease computation and communication cost for establishing the shared key between two nodes.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.24-30
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• 2001

The substructure synthesis method(SSM) is developed for overcoming disadvantages of the Finite Element Method(FEM). The concept of the SSM is as follows. After dividing a whole structure into several substructures, every substructures are analyzed by the FEM or experiment. The whole structure is analyzed by using connecting condition and the results of substructures. The concept of the transfer stiffness coefficient method(TSCM) is based on the transfer of the nodal stiffness coefficients which are related to force vectors and displacement vectors at each node of analytical mode1. The superiority of the TSCM to the FEM in the computation accuracy, cost and convenience was confirmed by the numerical computation results. In this paper, the author suggests an efficient vibration analysis method of structures by using the TSCM and the SSM. The trust and the validity of the present method is demonstrated through the numerical results for computation models.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.314-317
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• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3690-3713
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• 2019

According to the main group key management schemes logical key hierarchy (LKH), exclusion basis systems (EBS) and other group key schemes are limited in network structure, collusion attack, high energy consumption, and the single point of failure, this paper presents a group key management scheme for wireless sensor networks based on Lagrange interpolation polynomial characteristic (AGKMS). That Chinese remainder theorem is turned into a Lagrange interpolation polynomial based on the function property of Chinese remainder theorem firstly. And then the base station (BS) generates a Lagrange interpolation polynomial function f(x) and turns it to be a mix-function f(x)' based on the key information m(i) of node i. In the end, node i can obtain the group key K by receiving the message f(m(i))' from the cluster head node j. The analysis results of safety performance show that AGKMS has good network security, key independence, anti-capture, low storage cost, low computation cost, and good scalability.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.198-209
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• 2007

This paper provides a thorough study on shared segment protection (SSP) for mesh communication networks in the complete routing information scenario, where the integer linear program (ILP) in [1] is extended such that the following two constraints are well addressed: (a) The restoration time constraint for each connection request, and (b) the switching/merging capacity constraint at each node. A novel approach, called SSP algorithm, is developed to reduce the extremely high computation complexity in solving the ILP formulation. Basically, our approach is to derive a good approximation on the parameters in the ILP by referring to the result of solving the corresponding shared path protection (SPP) problem. Thus, the design space can be significantly reduced by eliminating some edges in the graphs. We will show in the simulation that with our approach, the optimality can be achieved in most of the cases. To verify the proposed formulation and investigate the performance impairment in terms of average cost and success rate by the additional two constraints, extensive simulation work has been conducted on three network topologies, in which SPP and shared link protection (SLP) are implemented for comparison. We will demonstrate that the proposed SSP algorithm can effectively and efficiently solve the survivable routing problem with constraints on restoration time and switching/merging capability of each node. The comparison among the three protection types further verifies that SSP can yield significant advantages over SPP and SLP without taking much computation time.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.239-244
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• 2007

In the telematics system, a reasonable path search time should be guaranteed from a great number of user's queries, even though the optimal path with minimized travel time might be continuously changed by the traffic flows. Thus, the path search method should consider traffic flows of the roads and the search time as well. However, the existing path search methods are not able to cope efficiently with the change of the traffic flows and to search rapidly paths simultaneously. This paper proposes a new path search method for fast computation. It also reflects the traffic flows efficiently. Especially, in order to simplify the computation of variable heuristic values, it employs a simplification method for estimating values of traffic-adaptable heuristics. The experiments are carried out with the $A^*$ algorithm and the proposed method in terms of the execution time, the number of node accesses and the accuracy. The results obtained from the experiments show that the method achieves very fast execution time and the reasonable accuracy as well.