METODE PENDEKATAN MENGHITUNG AGREGASI QUANTILE PADA SISTEM MANAJEMEN DATA DENGAN MENGGUNAKAN STRUKTUR POHON BINER

Query agregasi dalam system basis data telah banyak dibicarakan. Agregasi tersebut diantaranya adalah menghitung MIN, AVG, FREKUENSI dan estimasi QUANTILE. Dalam system basis data yang berbasis sensor pun beberapa metode telah banyak dikembangkan, metode ini digunakan untuk mengekstrak informasi yang berguna dari data dengan menggunakan sensor. Penghitungan agregasi ini dapat dijadikan metode routing dalam jaringan-agregasi, sehingga dapat mengurangi lalu lintas jaringan. Pada tulisan ini diusulkan metode menghitung estimasi QUANTILE dengan menggunakan struktur pohon biner pre order dan in order traversal kemudian dibandingkan dengan metode perhitungan estimasi quantile yang sudah ada yaitu post order traversal

Spectra: Robust Estimation of Distribution Functions in Networks

Distributed aggregation allows the derivation of a given global aggregate property from many individual local values in nodes of an interconnected network system. Simple aggregates such as minima/maxima, counts, sums and averages have been thoroughly studied in the past and are important tools for distributed algorithms and network coordination. Nonetheless, this kind of aggregates may not be comprehensive enough to characterize biased data distributions or when in presence of outliers, making the case for richer estimates of the values on the network. This work presents Spectra, a distributed algorithm for the estimation of distribution functions over large scale networks. The estimate is available at all nodes and the technique depicts important properties, namely: robust when exposed to high levels of message loss, fast convergence speed and fine precision in the estimate. It can also dynamically cope with changes of the sampled local property, not requiring algorithm restarts, and is highly resilient to node churn. The proposed approach is experimentally evaluated and contrasted to a competing state of the art distribution aggregation technique.Comment: Full version of the paper published at 12th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS), Stockholm (Sweden), June 201

Accurate and precise aggregation counting

AbstractAggregation counting is any procedure designed to solve the following problem: a number n of agents produces a fixed length binary message, and a central station produces an estimate of n from the bit-by-bit OR of the messages, which is therefore duplicate-insensitive. Such procedures are applicable to a situation where each of n independent sensors broadcasts the message to be used to estimate the count. A mathematically brilliant solution to this problem, due to Flajolet and Martin (1985) [1], is unfortunately affected by substantial bias and error. In this note we outline an alternative approach, which uses the Flajolet–Martin technique as a preparatory step and substantially reduces both error and bias. Specifically, the standard deviation of the count estimate drops from ∼110% to ∼20% of the estimated value

Hybrid Approach for Data Aggregation in WSN with Advance Security Protocol in NS2 Software

Energy efficiency is a crucial resource constrained WSN. Diverse techniques for example duty cycling, optimization energy scheduling and data aggregation are applied so that energy can be used minimum. In this research paper there are two main domains on which work carried out successfully. First one is data aggregation but data aggregation in our work is of two levels. Another domain was security because as we know in MANET security is not up to the mark that is why unauthorized person can access the data by deploying malicious note in our existing network. A robust analytical development of the proposed protocol is presented by using concept of two level data aggregation. Quiet satisfactory performance of the proposed algorithm is depicted. Data aggregation is attained by iteratively applying the proposed compression method at the cluster heads and on the other hand data aggregation scheme in the presence of a Multi-interface Multi-Channel Routing Protocol is tested. One important thing is that in a cluster. A node can be cluster head only single time after that new node will be cluster head. MMCR uses a metric defined by various parameters like throughput, end-to-end delay and energy utilization to select Multi-Point Relay nodes to forward data packets in each channel but keeping in mind that loss of packet or information must be reduced. Finally we can say that proposed algorithm is far better than existed protocol. Besides that RSA security algorithm for encryption and decryption also applied so that unauthorized person cannot access the information. There are various security algorithm available but selection must be appropriate as per desired application

Image transmission in sensor networks

Wireless sensor networks allow fine-grained monitoring of the environment. However, as sensors have physical limitations in energy, processing power, and memory, etc., techniques have to be developed to efficiently utilize the limited resource available in a sensor network. In this paper, we study the image tranmission problem in sensor networks. Cameras are installed in various locations of a wide area to take images of targeted objects. These images have to be sent back to a centralized server, which may be very far away from the cameras. Therefore, the images have to traverse the sensors hop by hop to the server. As images usually contain a large amount of data, if they are sent individually, the communication overheads will be huge. To reduce the overheads, we can pre-process the images in the sensors before sending them back to the server, but this pre-processing requires extra energy in the sensors. In this paper, we study how images can be efficiently transmitted through a sensor network. We aim at reducing the energy needed in transmitting the images while maintaining the quality of the combined image. © 2005 IEEE.published_or_final_versio

Fault-Tolerant Aggregation: Flow-Updating Meets Mass-Distribution

Flow-Updating (FU) is a fault-tolerant technique that has proved to be efficient in practice for the distributed computation of aggregate functions in communication networks where individual processors do not have access to global information. Previous distributed aggregation protocols, based on repeated sharing of input values (or mass) among processors, sometimes called Mass-Distribution (MD) protocols, are not resilient to communication failures (or message loss) because such failures yield a loss of mass. In this paper, we present a protocol which we call Mass-Distribution with Flow-Updating (MDFU). We obtain MDFU by applying FU techniques to classic MD. We analyze the convergence time of MDFU showing that stochastic message loss produces low overhead. This is the first convergence proof of an FU-based algorithm. We evaluate MDFU experimentally, comparing it with previous MD and FU protocols, and verifying the behavior predicted by the analysis. Finally, given that MDFU incurs a fixed deviation proportional to the message-loss rate, we adjust the accuracy of MDFU heuristically in a new protocol called MDFU with Linear Prediction (MDFU-LP). The evaluation shows that both MDFU and MDFU-LP behave very well in practice, even under high rates of message loss and even changing the input values dynamically.Comment: 18 pages, 5 figures, To appear in OPODIS 201

Fully decentralized computation of aggregates over data streams

In several emerging applications, data is collected in massive streams at several distributed points of observation. A basic and challenging task is to allow every node to monitor a neighbourhood of interest by issuing continuous aggregate queries on the streams observed in its vicinity. This class of algorithms is fully decentralized and diffusive in nature: collecting all data at few central nodes of the network is unfeasible in networks of low capability devices or in the presence of massive data sets. The main difficulty in designing diffusive algorithms is to cope with duplicate detections. These arise both from the observation of the same event at several nodes of the network and/or receipt of the same aggregated information along multiple paths of diffusion. In this paper, we consider fully decentralized algorithms that answer locally continuous aggregate queries on the number of distinct events, total number of events and the second frequency moment in the scenario outlined above. The proposed algorithms use in the worst case or on realistic distributions sublinear space at every node. We also propose strategies that minimize the communication needed to update the aggregates when new events are observed. We experimentally evaluate for the efficiency and accuracy of our algorithms on realistic simulated scenarios

EZ-AG: Structure-free data aggregation in MANETs using push-assisted self-repelling random walks

This paper describes EZ-AG, a structure-free protocol for duplicate insensitive data aggregation in MANETs. The key idea in EZ-AG is to introduce a token that performs a self-repelling random walk in the network and aggregates information from nodes when they are visited for the first time. A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often. While self-repelling random walks visit all nodes in the network much faster than plain random walks, they tend to slow down when most of the nodes are already visited. In this paper, we show that a single step push phase at each node can significantly speed up the aggregation and eliminate this slow down. By doing so, EZ-AG achieves aggregation in only O(N) time and messages. In terms of overhead, EZ-AG outperforms existing structure-free data aggregation by a factor of at least log(N) and achieves the lower bound for aggregation message overhead. We demonstrate the scalability and robustness of EZ-AG using ns-3 simulations in networks ranging from 100 to 4000 nodes under different mobility models and node speeds. We also describe a hierarchical extension for EZ-AG that can produce multi-resolution aggregates at each node using only O(NlogN) messages, which is a poly-logarithmic factor improvement over existing techniques

Prediction of time series using wavelet Gaussian process for wireless sensor networks

Articulo de investigacion idizado en JCR con factor de impacto 2.2The detection and transmission of a physical variable over time, by a node of a sensor network to its sink node, represents a significant communication overload and consequently one of the main energy consumption processes. In this article we present an algorithm for the prediction of time series, with which it is expected to reduce the energy consumption of a sensor network, by reducing the number of transmissions when reporting to the sink node only when the prediction of the sensed value differs in certain magnitude, to the actual sensed value. For this end, the proposed algorithm combines a wavelet multiresolution transform with robust prediction using Gaussian process. The data is processed in wavelet domain, taking advantage of the transform ability to capture geometric information and decomposition in more simple signals or subbands. Subsequently, the decomposed signal is approximated by Gaussian process one for each subband of the wavelet, in this manner the Gaussian process is given to learn a much simple signal. Once the process is trained, it is ready to make predictions. We compare our method with pure Gaussian process prediction showing that the proposed method reduces the prediction error and is improves large horizons predictions, thus reducing the energy consumption of the sensor network

ADA: Authenticated Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks are vulnerable to communication failures and security attacks. It is quite challenging to provide security to data aggregation. This paper proposes Authenticated Data Aggregation for Wireless Sensor Networks, where the nodes organize themselves into tiers around the sink. Message Authentication Code (MAC) is generated and transmitted along with the synopsis to ensure integrity. All nodes in the network store the same key that is used for rekeying operation during each round to generate MAC. Thus ADA ensures data freshness and integrity at a communication cost of O (1). Simulation results show that the proposed ADA protocol results in high security, low energy consumption and low communication cost compared to the state-of-the art protocol