Many recent wireless sensor network (WSN) routing protocols are enhancements to address specific issues with the “low-energy adaptive clustering hierarchy” (LEACH) protocol. Since the performance of LEACH deteriorates sharply with increasing network size, the challenge for new WSN protocols is to extend the network lifespan while maintaining high scalability. This paper introduces an energy-efficient clustering and hierarchical routing algorithm named energy-efficient scalable routing algorithm (EESRA). The goal of the proposed algorithm is to extend the network lifespan despite an increase in network size. The algorithm adopts a three-layer hierarchy to minimize the cluster heads’ load and randomize the selection of cluster heads. Moreover, EESRA uses multi-hop transmissions for intra-cluster communications to implement a hybrid WSN MAC protocol. This paper compares EESRA against other WSN routing protocols in terms of network performance with respect to changes in the network size. The simulation results show that EESRA outperforms the benchmarked protocols in terms of load balancing and energy efficiency on large-scale WSNs.

/pdf/eesra-energy-efficient-scalable-routing-algorithm-for-vytky3j57p.pdf

EESRA: Energy Efficient Scalable Routing Algorithm for Wireless Sensor Networks

Emerging technological advances in wireless communication and networking have led to the design of large scale networks and small sensor units with minimal power requirements and multifunctional processing. Though energy harvesting technologies are improving, the energy of sensors remains a scarce resource when designing routing protocols between sensor nodes and base station. This paper proposes a multi-hop graph-based approach for an energy-efficient routing (MH-GEER) protocol in wireless sensor networks which aims to distribute energy consumption between clusters at a balanced rate and thus extend networks’ lifespans. MH-GEER deals with node clustering and inter-cluster multi-hop routing selection. The clustering phase is built upon the centralized formation of clusters and the distributed selection of cluster heads similar to that of low-energy adaptive clustering hierarchy (LEACH). The routing phase builds a dynamic multi-hop path between cluster heads and the base station. Our strategy is about exploring the energy levels in the entire network and using these to select the next hop in a probabilistic, intelligent way. Performance evaluation shows that MH-GEER minimizes energy depletion in distant clusters and ensures load balancing in a network, thus improving the network’s lifetime and stability compared with single-hop conventional LEACH protocol.

/pdf/a-multi-hop-graph-based-approach-for-an-energy-efficient-2z60vki21a.pdf

A multi-hop graph-based approach for an energy-efficient routing protocol in wireless sensor networks

A wireless location-based gas detection system and method includes a gas detector for wirelessly detecting location information associated with a hazardous gas event. The gas detector includes one or more remote gas sensors that monitor for the occurrence of a gas event and wirelessly communicates information with respect to the location of the event in association with time information to a server or location manager. A wireless communication device in association with one or more location anchor points periodically and under event conditions, transmits the location information and the gas concentration level. A location engine calculates an estimated location of the gas detector based on information received from the wireless communication device and provides the location data to the location manager. The location manager records the gas concentration level, the estimated location, and the time information and stores this information within a database. A graphical user interface is provided for visualizing the current and historical information.

Wireless location-based system and method for detecting hazardous and non-hazardous conditions

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot`s playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers` communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

Chatting Pattern Based Game BOT Detection: Do They Talk Like Us?

A new energy aware cluster head selection for LEACH in wireless sensor networks

In order to effectively curb the effect of complex environment on the accuracy of position of nodes in Wireless Sensor Network, an anchor node weighted compensated localization algorithm is proposed, based on the trilateration localization algorithm and the centroid localization algorithm. By using the anchor node's own locating capabilities as well as the weighted centroid localization algorithm, the proposed algorithm can obtain the locating error of the region nearby the anchor node. When calculating the coordinates of blind node in this region, the algorithm can compensate for this error, thereby enhancing the locating accuracy of blind nodes. Experiment results show that the average locating accuracy is about 2m. Without any need for extra hardware consumption, this algorithm is simple, effective and can be widely applied.

A weighted compensated localization algorithm of nodes in Wireless Sensor Networks

In order to minimize energy dissipation and maximize network lifetime, a new energy-efficient algorithm (LEACH-WM) based on weight and intra-cluster multi-hop mechanism is proposed in this paper. In the steady phase of LEACH-WM, a weight relay is elected in the cluster according to member nodes' residual energy and their distances away from the base station (BS).Cluster head sends aggregation data to its weight relay, which then forwards data to the BS. This process minimizes energy dissipation of the cluster head. The above mechanism distributes energy dissipation more uniformly in the network and further prolongs network life time. Simulations show that LEACH-WM does make alive nodes and dead nodes distribute more evenly in the network and it outperforms LEACH, LEACH-DCHS (Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection) and TB-LEACH (A Time-based Cluster-Head Selection Algorithm for LEACH)in terms of network lifetime and energy dissipation.

LEACH-WM: Weighted and intra-cluster multi-hop energy-efficient algorithm for wireless sensor networks

There are some common problems, such as low location accuracy and low sampling efficiency, existing in the present node localization algorithms that are based on Monte Carlo Localization (MCL) in mobile wireless sensor networks. To improve these issues, a Monte Carlo box localization algorithm based on RSSI(MCBBR) is proposed in this paper. In the algorithm, sampling box was constructed through RSSI ranging as the optimal space for location estimation, sample number was adaptive according to the size of sampling box, and genetic algorithm method was referenced to optimize samples. Finally the mean value of all samples was the optimal location estimation. Simulation results show that the proposed algorithm can enhance the location accuracy by 30% comparing to MCB algorithm, and 10% comparing to Range-Based MCL algorithm. Furthermore, the results also show that the algorithm can achieve a higher sampling efficiency. Thus, MCBBR can be applied in the circumstance where the high location accuracy and sampling efficiency are required.

A Monte Carlo box localization algorithm based on RSSI

The utility model discloses a wireless multimedia broadband sensor network node device comprising a processor unit (1), a storage unit (2), a video unit (3), a audio unit (4), a display unit (5), a wireless communication unit (6), a debugging unit (7) and a power supply unit (8); wherein the video unit (3) is used for acquiring a video signal; the audio unit (4) is used for acquiring and playing a audio signal; the wireless communication unit (6) is used for sending and receiving a signal; the debugging unit (7) is used for program debugging of the wireless multimedia broadband sensor network node device; and the power supply unit (8) is used for providing a working voltage for the whole device The wireless multimedia broadband sensor network node device of the utility model effectively solves the problems that a traditional wireless sensor network system can not effectively acquire and transmit audio and video signals, and has the disadvantages of weak processing capability, narrow bandwidth and so on, in addition, the wireless multimedia broadband sensor network node device also has the advantages of low investment cost, high cost performance, good real-time performance, safety, reliability, and convenient use and maintenance

Wireless multimedia broadband sensor network node device

Time synchronization is one of the fundamental techniques for the wireless sensor networks to obtain the real-time effective information. The security of this technology is becoming increasingly important. In this paper, we analyze the security of RBS, the synchronization algorithm in WSN, point out the potential vulnerabilities existing in the algorithm, and propose optimization on security for the algorithm. Simulation result shows improved algorithm not only defends external attacks effectively, but greatly reduces the effects of internal attack.

Enhancement of the security of RBS for wireless sensor networks

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