Department of Computer Science and Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

In this paper, we describe a method to predict emotion intensity in tweets. Our approach is an ensemble of three regression methods. The first method uses content-based features (hashtags, emoticons, elongated words, etc.). The second method considers word n-grams and character n-grams for training. The final method uses lexicons, word embeddings, word n-grams, character n-grams for training the model. An ensemble of these three methods gives better performance than individual methods. We applied our method on WASSA emotion dataset. Achieved results are as follows: average Pearson correlation is 0.706, average Spearman correlation is 0.696, average Pearson correlation for gold scores in range 0.5 to 1 is 0.539, and average Spearman correlation for gold scores in range 0.5 to 1 is 0.514. © 2017 Association for Computational Linguistics.

World University root node

EMNLP 2017 - 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2017 - Proceedings of the Workshop

NSEmo at EmoInt-2017: An ensemble to predict emotion intensity in tweets

Nowadays online social networks are used extensively for personal and commercial purposes. This widespread popularity makes them an ideal platform for advertisements. Social media can be used for both direct and word-of-mouth (WoM) marketing. Although WoM marketing is considered more effective and it requires less advertisement cost, it is currently being under-utilized. To do WoM marketing, we need to identify a set of people who can use their authoritative position in social network to promote a given product. In this paper, we show how to do WoM marketing in Facebook group, which is a question answer type of social network. We also present concept of reinforced WoM marketing, where multiple authorities can together promote a product to increase the effectiveness of marketing. We perform our experiments on Facebook group dataset consisting of 0.3 million messages and 10 million user reactions. © 2017, Springer International Publishing AG.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Using social media for word-of-mouth marketing

The non-uniform distribution of memory accesses among the cache sets results in some sets being used heavily while certain others remaining underutilized. Dynamic associativity management (DAM) is a technique to allow the heavily used sets to distribute their load among the lightly used sets thus improving the overall utilization of the cache. CMP-SVR is a previously proposed DAM based technique, where each set is divided into two sections: normal storage (NT) and reserve storage (RT). Some number of ways (25 to 50 percent) from each set are reserved for RT and the remaining ways belong to NT. The sets are divided into groups called fellow-groups and a set can use the reserve-ways of its fellow sets to increase its associativity during execution. Though CMP-SVR improves performance the formation of its fellow-groups is static: once created it never changes. It has been observed that some fellow-groups have more number of heavily used sets than the other fellow-groups. As a result the cache loads are not uniformly distributed among the fellow-groups. Also the behavior of sets changes dynamically: a lightly used set may become heavily used after a number of execution cycles. This paper studies the behavior of each set in detail and proposes a DAM based technique which improves the performance compared to other DAM based techniques. The proposed technique called FS-DAM dynamically creates fellow-groups based on the current set loads ensuring that the heavily used sets are evenly distributed among all the fellow-groups. Such distribution increases the utilization of the cache and hence improves performance. Full system simulation shows an average of 6.62 and 16.74 percent improvements, in FS-DAM as compared to CMP-SVR, in terms of CPI (Cycles Per Instruction) and MPKI (Miss Per Thousand Instructions) respectively. Comparing with Z-Cache the improvements are 6.21 percent (CPI) and 14.65 percent (MPKI). The proposed policy also shows better performance over V-Way and SBC. © 1990-2012 IEEE.

IEEE Transactions on Parallel and Distributed Systems

Dynamic Associativity Management in Tiled CMPs by Runtime Adaptation of Fellow Sets

Online social media provide a platform for rapid network propagation of information at an unprecedented scale. In this paper, we study the evolution of information cascades in Twitter using a point process model of user activity. Twitter is rich with heterogenous information on users and network structure. We develop several Hawkes process models considering various properties of Twitter including conversational structure, users’ connections and general features of users including the textual information, and show how they are helpful in modeling the social network activity. Evaluation on Twitter data sets shows that incorporating richer properties improves the performance in predicting future activity of users and memes. © 2017 Association for Computing Machinery.

Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

Longitudinal modeling of social media with hawkes process based on users and networks

In this paper, we present multi-threaded algorithms for graph coloring suitable to the shared memory programming model. Initially, we describe shared memory implementations to the algorithms widely known in the literature like Jones Plassman graph coloring. Later, we propose new approaches to solve the problem of coloring using mutex locks while making sure that deadlocks do not occur. Using datasets from real world graphs, we evaluate the performance of all these algorithms on the Intel platform. We compare the performance of sequential graph coloring v/s our proposed approaches and analyze the speedup obtained against the existing algorithms from the literature. The results show that the speedup obtained by our proposed algorithms in terms of the time taken for coloring is consequential. We also provide a direction for future work towards improving the performance further in terms of different metrics. © 2017 ACM.

ACM International Conference Proceeding Series

Practical multi-threaded graph coloring algorithms for shared memory architecture

In order to ensure the safety measures, the detection of traffic rule violators is a highly desirable but challenging task due to various difficulties such as occlusion, illumination, poor quality of surveillance video, varying whether conditions, etc. In this paper, we present a framework for automatic detection of motorcyclists driving without helmets in surveillance videos. In the proposed approach, first we use adaptive background subtraction on video frames to get moving objects. Later convolutional neural network (CNN) is used to select motorcyclists among the moving objects. Again, we apply CNN on upper one fourth part for further recognition of motorcyclists driving without a helmet. The performance of the proposed approach is evaluated on two datasets, IITH-Helmet-1 contains sparse traffic and IITH-Helmet-2 contains dense traffic, respectively. The experiments on real videos successfully detect 92.87% violators with a low false alarm rate of 0.5% on an average and thus shows the efficacy of the proposed approach. © 2017 IEEE.

Proceedings of the International Joint Conference on Neural Networks

Detection of motorcyclists without helmet in videos using convolutional neural network

Multipath TCP (MPTCP) brings promising features of throughput improvement and load balancing by utilizing the multiple available paths. However, adding a subflow without awareness of the network state will result in wasting network resources and degrading MPTCP performance. Finding and operating the proper number of subflows are necessary to achieve the best performance of MPTCP. However, an MPTCP host does not have knowledge about the number of available paths in the network, and it may create the suboptimal number of subflows. This paper proposes SubFlow Optimizer (SFO) for MPTCP in SDN that estimates the Optimum Number of Subflows (ONS) and informs it to the MPTCP hosts. The estimated ONS reflects the number of optimal paths found out of the set of feasible paths between the server and client. Selecting such an optimal path for a new subflow improves its throughput whereas detecting ONS makes efficient use of the overall network. SFO also enables the quick negotiation of ONS between MPTCP hosts during its session establishment that reduces the time required for ONS negotiation down to one Round-Trip Time (RTT). Therefore, MPTCP hosts can immediately achieve the best performance without incremental try and catch of subflow creation. The results of performance evaluation show that SFO brings the significant throughput improvement to the overall MPTCP session compared with the cases of improper estimation of the available number of subflows. © 2016 IEEE.

26th International Telecommunication Networks and Applications Conference, ITNAC 2016

SFO: SubFlow Optimizer for MPTCP in SDN

The handover algorithms implemented in Network Simulator-3 (A3RSRP and A2A4RSRQ) for Long Term Evolution (LTE) so far, under certain scenarios, fail to prevent unnecessary handovers like ping-pong handovers which may lead to poor channel quality. To address this issue, we present A1A3RSRP (based on Reference Signal Received Power (RSRP)) and A1A2A4RSRPRSRQ (based on both RSRP and Reference Signal Received Quality (RSRQ)) handover algorithms. The primary objective of these algorithms is to reduce the number of unnecessary handovers such as ping-pong handovers which diminish the network performance. We compare and provide statistical analysis for these algorithms using various metrics and show that in a topology which induces ping-pongs, A1A3RSRP reduces the number of ping-pong handovers by an average of 33.33% as compared to A3RSRP and increases the average aggregate system throughput by an average of 3.43%. With the same topology, A1A2A4RSRPRSRQ reduces the number of ping-pong handovers by an average of 50% as compared to A2A4RSRQ and increases the average aggregate system throughput by an average of 3.38%. Also, on a realistic topology, A1A3RSRP reduces the number of ping-pong handovers by an average of 1.75% as compared to A3RSRP while maintaining the same average aggregate system throughput. In this topology, A1A2A4RSRPRSRQ reduces the number of ping-pong handovers by an average of 6.45% as compared to A2A4RSRQ without compromising the average aggregate system throughput. © 2017 IEEE.

2017 23rd National Conference on Communications, NCC 2017

Reducing ping-pong handovers in LTE by using A1-based measurements

Tight coupling of LTE and Wi-Fi networks is accomplished by binding their protocol stacks. LTE Wi-Fi radio level integration with IPSec tunnel (LWIP) corresponds to realizing this binding at IP layer. A collocated deployment of LWIP enables greater flexibility in utilizing the channel efficiently. With the advent of bandwidth-hungry smartphone Apps and IoT applications, the cellular uplink resources become highly demanding. This enforces Wi-Fi to support efficient uplink transmissions since the uplink transmissions through Wi-Fi suffers high contention because of distributed nature of Wi-Fi MAC. In order to improve Wi-Fi channel utilization by leveraging the potential of LWIP in controlling and coordinating the transmissions through LTE and Wi-Fi links, we introduce Network Coordination Function (NCF) in LWIP. The proposed NCF focuses on coordinating the uplink transmissions through Wi-Fi in a network with high load. NCF enhances the channel utilization of Wi-Fi network by regulating the packet arrival rate to the Wi-Fi link and also by revamping medium access techniques at the Wi-Fi interface of users associated with LWIP node. NCF is composed of four different uplink traffic steering algorithms with diverse objectives which improve Wi-Fi channel utilization by (i) minimizing collisions among LWIP users, (ii) increasing transmission opportunities for Wi-Fi users that are connected to legacy Wi-Fi APs operating on the same channel, and (iii) ensuring fairness for both LWIP and Wi-Fi users. Interestingly, NCF has not only improved the throughput of LWIP users but also the throughput of Wi-Fi users. Simulation experiments reveal that NCF has reduced collisions in the Wi-Fi uplink by 13–53% and improved throughput by 10–37% as compared to Wi-Fi offloading and Distributed Coordination Function (DCF). © 2017 Elsevier B.V.

Fulltext

Computer Networks

Network Coordination Function for uplink traffic steering in tightly coupled LTE Wi-Fi networks

Downlink/Uplink decoupling (DUDe) in LTE networks has caught the attention of researchers as it provides better uplink SINR and reduced power consumption per device due to decoupled connection of a device with the Macro (in downlink) and a small cell (in uplink). These characteristics of DUDe can be exploited to encourage more D2D communications in the network. This paper first proposes a model to estimate decoupling region within which a device is allowed to perform DUDe. Then, it formulates an equation to calculate the total power saved by devices due to decoupling. Finally, the extra area due to decoupling which can be used to enable D2D pairs is calculated. Simulation results are shown based on different simulation scenarios for different objectives for better understanding the idea proposed. © 2016 IEEE.