Joonmo Kim

The complexity of influence maximization problem in the deterministic linear threshold model

The influence maximization is an important problem in the field of social network. Informally it is to select few people to be activated in a social network such that their aggregated influence can make as many as possible people active. Kempe et al. gave a

LAID: load-adaptive internet gateway discovery for ubiquitous wireless internet access networks

(1-{1 \over e})

PTAS for the minimum weighted dominating set in growth bounded graphs

-approximation algorithm for this problem in the linear threshold model and the independent cascade model. In addition, Chen et al. proved that the exact computation of the influence given a seed set is #P-hard in the linear threshold model. Both of the two models are based on randomized propagation, however such information might be obtained by surveys and data mining techniques. This will make great difference on the complexity of the problem. In this note, we study the complexity of the influence maximization problem in deterministic linear threshold model. We show that in the deterministic linear threshold model, there is no n1−ε-factor polynomial time approximation for the problem unless P=NP. We also show that the exact computation of the influence given a seed set can be solved in polynomial time.

Weighted localized clustering: a coverage-aware reader collision arbitration protocol in RFID networks

Ubiquitous Internet connectivity is to connect all devices to the Internet at any time and any place To achieve this ubiquitous Internet connectivity, we consider integrating the Internet and mobile ad-hoc networks One of the most important issues in the ubiquitous Internet connectivity is to find an efficient and reliable Internet gateway We propose a load-adaptive Internet gateway discovery approach that can exploit network conditions The load-adaptive Internet gateway discovery scheme dynamically adjusts a proactive area according to network traffic Among the candidates, a serving gateway is selected based on offered load The simulation results show that our discovery scheme outperforms existing discovery schemes.

Stability of Game-Theoretic Energy-Aware MAC Scheme for Wireless Sensor Networks

The minimum weighted dominating set (MWDS) problem is one of the classic NP-hard optimization problems in graph theory with applications in many fields such as wireless communication networks. MWDS in general graphs has been showed not to have polynomial-time constant-approximation if

Cost-based join processing scheme in a hybrid RDBMS and hive system

{\mathcal{NP} \neq \mathcal{P}}

A NOTE ON BALANCED HOWELL ROTATIONS FOR TWIN PRIME POWER TYPE

. Recently, several polynomial-time constant-approximation SCHEMES have been designed for MWDS in unit disk graphs. In this paper, using the local neighborhood-based scheme technique, we present a PTAS for MWDS in polynomial growth bounded graphs with bounded degree constraint.

A study on monitoring and protecting computer system against interception threat

This paper addresses a weighted localized scheme and its application to the hierarchical clustering architecture, which results in reduced overlapping areas of clusters. Our previous proposed scheme, Low-Energy Localized Clustering (LLC), dynamically regulates the radius of each cluster for minimizing energy consumption of cluster heads (CHs) while the entire network field is still being covered by each cluster in sensor networks. We present weighted Low-Energy Localized Clustering(w-LLC), which has better efficiency than LLC by assigning weight functions to each CH. Drew on the w-LLC scheme, weighted Localized Clustering for RFID networks(w-LCR) addresses a coverage-aware reader collision arbitration protocol as an application. w-LCR is a protocol that minimizes collisions by minimizing overlapping areas of clusters.