Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Subject: search.filters.subject.Graph algorithms

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Modified MapReduce framework for enhancing performance of graph based algorithms by fast convergence in distributed environment
    (Institute of Electrical and Electronics Engineers Inc., 2014) Singhal, H.; Guddeti, G.R.M.
    The amount of data which is produced is huge in current world and more importantly it is increasing exponentially. Traditional data storage and processing techniques are ineffective in handling such huge data [10]. Many real life applications require iterative computations in general and in particular used in most of machine learning and data mining algorithms over large datasets, such as web link structures and social network graphs. MapReduce is a software framework for easily writing applications which process large amount of data (multi-terabyte) in parallel on large clusters (thousands of nodes) of commodity hardware. However, because of batch oriented processing of MapReduce we are unable to utilize the benefits of MapReduce in iterative computations. Our proposed work is mainly focused on optimizing three factors resulting in performance improvement of iterative algorithms in MapReduce environment. In this paper, we address the key issues based on execution of tasks, the unnecessary creation of new task in each iteration and excessive shuffling of data in each iteration. Our preliminary experiments have shown promising results over the basic MapReduce framework. The comparative study with existing solutions based on MapReduce framework like HaLoop, has also shown better performance w.r.t algorithm run time and amount of data traffic over Hadoop Cluster. © 2014 IEEE.
  • No Thumbnail Available
    Item
    Minimizing the total range with two power levels in wireless sensor networks
    (Springer Verlag service@springer.de, 2019) Shetty D, D.; Lakshmi, M.
    Minimizing the total energy consumed by wireless sensor network (WSN) is a significant problem, since the sensor nodes are attached with a small battery of restricted capacity. In a WSN, any pair of sensor nodes must be able to communicate with each other in the network, so bidirectional connectivity of WSN is an important characteristic to be achieved. The range assignment problem in a WSN aims to assign transmission range to each sensor node of the network such that the specified connectivity constraints such as strong connectivity, k-connectivity are to be satisfied by the reduced network. Most sensors in recent days operate with discrete power levels. So, in this paper, we consider the range assignment problem with two power levels. Our aim is to assign each sensor node in the network with one of the available set of power levels such that the reduced topology is strongly connected and the total power consumption is minimized. The dual power assignment problem is well studied in the literature. We present an improved algorithm for dual power assignment problem in which the power levels are taken as input. Performance of the proposed algorithms is analyzed through extensive simulation. We establish the theoretical approximation ratio bound of the proposed algorithm for dual power assignment problem as 2. But, the simulation results indicate that the performance ratio is much less than 2. © 2019, Springer Nature Singapore Pte Ltd.