Parallel Session 1
Saturday, July 17 11:30 - 1:00
11:30 Traffic-aware Link Assignment in GEO Satellite Communication Networks
Due to the advantages of global coverage, large capacity and support for remote area and emergency communication, satellite communications have play an important role in civil and military fields. To improve communication system performance, constructing satellite network through inter-satellite link (ISL) is an important way. As the ISL number of satellite is limited, reasonable link assignment is critical to achieve good performance. Most of existing related works adopt simplified theoretical network model. In this paper, we construct a more realistic satellite Geosynchronous Earth Orbit (GEO) network model which takes the visibility of satellites, antenna number and pointing into consideration. Besides, we formulate a traffic-aware link assignment problem based on the model and propose a heuristic algorithm to solve it. Simulation results show that the proposed algorithm costs less time to transmit traffic than usual fixed link assignment patterns. Moreover, through changing the weights different services, we can adjust their transmission time.
11:45 Orbit Shifting Analysis Satellite Telkom 4 with Cowell and Encke Method Caused by Perturbation
Satellites are objects that revolve around other objects in certain period of revolution and rotation. There are two types of satellites, natural and artificial satellites. There are several types of artificial satellites based on their use such as weather satellites, military satellites, science education satellites, and communications satellites. Artificial satellites can follow a position according to the movement of the earth, which is called the geostationary orbital position. When a satellite is in a geostationary orbit position, its speed will be relatively low, allowing the position satellite to be moved. The surveillance area has been regulated in ITU-R Rec. S. 484. about the control area tolerance limit of less ±0,5° for operational fixed satellite. In this case, the mobile satellite requires a lot of power and shortens the life of the satellite. Predicting the orbital displacement time interval involves two orbital methods, namely Cowell method and Encke method. Both of these methods can be used to determine the length of time that occurs when the satellite is moved. This study aims to compare which method can determine time intervals more accurately. The advantage of this research is that there are two methods that can be used to determine the time interval of the satellite orbitals. Quantitative comparative research method for field survey through comparison of applied research in main control satellites. The results of the comparison of the two methods will be used for orbital purposes, combined with positional and mathematical factors to determine the duration of orbital shift.
12:00 A Novel Elman Network based INS/GPS Fusion Filter to Enhance Tracking Accuracy in UAVs
Development of a highly accurate position tracking technique for extremely nonlinear dynamic systems such as unmanned aerial vehicles (UAV) using integrated global positioning system (GPS) and inertial navigation system (INS) is a challenging problem. During GPS outages, the existing systems experience considerable errors. In this paper, we propose a novel fusion algorithm based on an extended Kalman filter (EKF) – Elman neural network (ENN) that is capable of enhancing the tracking accuracy during GPS outages. The proposed technique relates the INS outputs from the sensors to the GPS position increment. ENN corrects the system during GPS-outages by predicting the pseudo
GPS position. The time information is also considered to obtain precise estimates and also to reduce the computational complexity. Simulation studies are performed on a UAV trajectory using low-cost MEMS-INS sensors to test the robustness of the algorithm under extreme varieties. The proposed system shows a reduction in root mean square error(RMSE) of the estimated position compared to the existing back propagation neural network(BPNN) model.
12:15 Techno-Economic of the Ka-Band HTS to Minimize Broadband Services Gap for Indonesian Government
Satellite technology has a vital role in delivering big archipelagic country communication services, including Indonesia, for many years. It is not surprising that there are many satellites above Indonesia regions, either foreign or Indonesian satellites. From those satellites, the majority of them still use conventional satellites in C or Ku Bands. As time goes by, these C and Ku Band’s use is very limited in generating channel capacity to extend the capacity for responding to the massively increasing number of capacity demand in the broadband era. This paper discussed the potential use of the next generation high throughput satellite (HTS) in the Ka-Band frequency spectrum using a techno-economic analysis perspective. The technical result shows that it potentially fulfill 114.67 – 1,031.51 Gbps using 244 beams (61 Frequency Reuse Factor). Then, the economic result obtained the NPV of Rp13,168,414,276,316.20 (positive value > 0), the IRR of 15% (more than WACC), the profitability Index of 2.94 (greater than 1), and the HTS implementation can reach a payback period of around nine years two months.
12:30 Implementation of Layer 2 MPLS VPN on the SDN Hybrid Network using Ansible and ONOS Controllers
L2VPN AToM (Any Transport over MPLS) is an ethernet-based private communication service that can connect networks in different geographical locations but seems to be on the same network logically through MPLS networks on the same bridge domain. L2VPN AToM technology is a consideration in enterprise networks to manage the availability of data sources centrally, safely, and quickly with other branch offices. L2VPN AToM becomes inefficient and inflexible in the management of large networks that are formed between the head office and branch offices which must be configured manually one by one as many as the number of branch offices to be connected. In managing the configuration of the L2VPN AToM network it can be done centrally to improve network efficiency by using the SDN architecture. However, this architecture requires a long time in the transition process and considering the costs incurred to replace conventional network devices that are already operating. For the solution, Hybrid SDN (Software Defined Network) network technology is needed as a solution to centrally manage conventional networks. Hybrid SDN Network is a technology that separates the control plane and the data plane by utilizing conventional network devices to be applied to the SDN architecture. This research used ansible as a controller that will distribute conventional network configuration centrally and an ONOS controller as a traffic management service for L2VPN AToM traffic. The research result shows that Hybrid SDN networks are better than using conventional networks with different average values of throughput in 3.12%, 2.12% of delay, and 0.3% of packet loss.
11:30 Mapping of Business Intelligence Research Themes: Four Decade Review
Research on business intelligence continues to develop but is limited to one country and/or one field. From the perspective of bibliometric reviews, this study purposes to visually research mapping and research trends in the field of business intelligence on an international scale. This study used bibliometric techniques with secondary data from Scopus. Analyze and visualize data using the VOSViewer program and the analyse search results function on Scopus. This study analyzed 244 scientific documents published from 1975 to 2020. According to the research, Monash University, and Yeoh, W. had the most active affiliated institutions and individual scientists in business intelligence research. Business, management, and accounting; and Lecture Notes in Business Information Processing were the most studied and disseminated outlets of business intelligence research. There were five category maps of collaborative researchers from around the world. Based on the identification of a collection of knowledge accumulated from over forty-five years of publication, this research proposes a grouping of business intelligence research themes: Business analytics, Element of marketing, Competitive intelligence, Intelligence system, Industry, and Business process abbreviated as BECIIB themes.
11:45 Expert System of Land Suitability for Fruit Cultivation Using Case-Based Reasoning Method
Agriculture is one of the economic sectors in Indonesia that has the potential to be developed to support the achievement of the nation’s food independence. Horticultural farming has great opportunities to be developed. However, there are problems in the productivity and management of existing gardens. An example is the empty plot of land because often the planted plants can not survive, especially when the dry season arrives. Lack of information about land suitability and the limited ability of garden extension about the condition of land characteristics is the cause of the problem that occurs. This research aims to design and implement an expert system of land suitability selection for fruit crops. The method used for problem-solving using case-based reasoning is to compare new cases with old cases and calculate case similarity values. The result of this study is an expert system of determining the suitability of land for the cultivation of fruit crops that can provide recommendations on what plants are suitable for the land analyzed. The proposed case-based reasoning method can analyze the condition of the land by taking into account the conditions with their respective weights. Accuracy testing using the cyclomatic complexity method obtained expert system accuracy obtained results of 80% of 30 test cases.
12:00 Performance Comparison of Swarm Intelligence Algorithms for Web Caching Strategy
Web caching is one strategy that can be used to speed up response times by storing frequently accessed data in the cache server. Given the cache server limited capacity, it is necessary to determine the priority of cached data that can enter the cache server. This study simulated cached data prioritization based on an objective function as a characteristic of problem-solving using an optimization approach. The objective function of web caching is formulated based on the variable data size, count access, and frequency-time access. Then we use the knapsack problem method to find the optimal solution. The Simulations run three swarm intelligence algorithms ACO, GA, and BPSO, divided into several scenarios. The simulation results show that the GA algorithm relatively stable and fast to convergence. The ACO algorithm has the advantage of a non-random initial solution but has followed the pheromone trail. The BPSO algorithm is the fastest, but the resulting solution quality is not as good as ACO and GA.
12:15 Implementation of Constant-Q Transform (CQT) and Mel Spectrogram to converting Bird’s Sound
Classification of bird sounds can be done in various methods and ways. One method that can be used is CNN (Convolutional Neural Network). CNN is an algorithm used for image classification. For bird sounds to be classified by CNN, conversion from analogue sound to digital images is required objectively and accurately. This study will discuss the conversion of analogue sound from birds into spectrogram images using one of Constant-Q Transform (CQT) and Mel Spectrogram. Bird voices are recorded using a voice recorder. The recorded voice will represent the audio signal digitally. Constant-Q Transform will map the audio signal from a time domain to a frequency domain. The frequency will be converted into a log scale and the colour dimensions (amplitude) into decibels to form a spectrogram. The spectrogram will be mapped on a mel scale to form a mel spectrogram. This research is the change of bird’s voice analogously to mel spectrogram, classified in CNN. The resulting images from this study can be classified using CNN to help classify bird sounds
12:30 Fuzzy Logic Implementation on Motion of Tennis Ball Picker Robot
The role of the tennis ball picker robot is to work to pick up tennis balls that are on the court after they are not used in a match. The tennis ball picker robot is an implementation of a vision-based robot designed to use object tracking techniques in tracking an object by utilizing digital image processing. This process gives the robot the ability to know the motion of the tennis ball. In this research, the robot will track the position of a tennis ball which has the characteristics of color, shape and size. Pixy2 CMUcam5 image sensor use to detect the tennis ball, while to control the position of the robot uses the fuzzy logic method. Input from fuzzy logic is the x and y coordinate points of the tennis ball’s position towards the robot. The output of the fuzzy logic is the speed of the motor actuator on the robot wheel to move the robot to detected tennis ball position. Infrared sensor can detect tennis ball as far as 100 cm and tennis ball position point is detected by Pixy2 CMUcam5 camera sensor at coordinates (169, 170). By using the fuzzy logic method the robot can pick up a tennis ball at the 7th second.
12:45 Personality Detection on Social Media Twitter Using Long Short-Term Memory with Word2Vec
Personality is one of the things that exist in every
human being. From this personality, it will be seen that humans
are unique and diverse individuals. One of the causes is because
each human being has a personality. This personality will create
humans to have a way of thinking and behave. Personality can
also be a benchmark or valuation. For example in applying for
work, some companies will have standards such as the workers
they will recruit. One tool for doing this is a psychological test.
But the drawback of this psychological test method is that it
takes a long time. So we created a system that can predict
someone based on the person’s tweet data on Twitter. Because
Twitter tweet contains many of opinions or thoughts of these user
that can describe how the user personality. The methods we use
are Word2Vec and LSTM (Long Short-Term Memory). Because
we use dataset that contains collection of tweet and LSTM can
remembering the past information while doing the prediction.
The system that we create it’s focus to see how collection of
tweet can predict the user personality. The first scenario it’s
to combine every 2 row of tweet and have accuracy 45% and
second combine 10 tweet and have the best accuracy it’s 48%.
The system using 5 labels personality that we called Big Five
11:30 5G D2D Transmission Mode Selection Performance & Cluster Limits Evaluation of DAI and ML Techniques
5G D2D Communication promises improvements in
energy and spectral efficiency, overall system capacity, and higher
data rates. However, to achieve optimum results, it is essential to
select wisely the Transmission mode of the D2D Device to form
clusters in the most advantageous positions in terms of Sum Rate
and Power Consumption. Towards this end, this paper investigates
the use of Distributed Artificial Intelligence (DAI) and innovative
D2D, Machine Learning (ML) approaches (i.e., DAIS, FuzzyART,
DBSCAN and MEC) to achieve satisfactory results in terms of
Spectral Efficiency (SE), Power Consumption (PC) and execution
time, with the creation of clusters and back-hauling links in D2D
network under existing Base Station. Additionally, this paper
focuses on a small number of Devices (i.e., <=200), targeting the identification of the limits of each approach in terms of the low number of devices. More specifically, we investigate when an operator must consider implementing a D2D network (that requires extra complexity), therefore when the cluster members are sufficient enough to achieve better results than the classic mobile network. So, this research identifies where it is beneficial to form a cluster, investigate the critical point that gains increases rapidly and in the end, examine the applicability of 5G requirements. Additionally, prior work presented a Distributed Artificial Intelligence (DAI) Solution/Framework in D2D, and a DAIS Transmission Mode Selection (TMS) plan was proposed. In this paper, DAIS is further examined, improved in terms of thresholds evaluation (i.e., Weighted Data Rate (WDR), Battery Power Level (BPL)), evaluated, and compared with other approaches (AI/ML). The results obtained demonstrate the exceptional performance of DAIS and FuzzyART, compared to all other related approaches in terms of SE, PC, execution time and cluster formation. Also, results show that the investigated AI/ML approaches are also beneficial for Transmission Mode Selection (TMS) in 5G D2D communication, even with fewer devices (i.e., >=5 for clustering,
>=50 for back-hauling) as lower limits.
11:45 Collaborative Traffic Measurement Using Sketches for Software Defined Networks
In a software-defined network (SDN), statistics information is of vital importance for different applications, such as traffic engineering, flow rerouting, and attack detection. Since some resources, e.g., ternary content addressable memory, SRAM, and computing capacity, are often limited in SDN switches, traffic measurements based on flow tables or sampling become infeasible. Sketch, a hash-based data structure, monitors every packet with fixed-size memory to provide a feasible approach of traffic measurement, but there exists a tradeoff between accuracy and memory. Currently, many efficient sketch algorithms have been designed to different purposes, but they focus on the performance of one single sketch. In this paper, we present a scheme to reduce redundant flow statistics collected by sketches of different SDN switches. The proposed scheme could reduce measurement overhead in sketches, obtain more accurate estimate flow size, and find the elephant flow precisely.
12:00 Adaptive Replication for Real-Time Applications based on Mobile Edge Computing
With the popularity of mobile devices, data transmission between mobile devices and cloud datacenters not only introduces tremendous data computation and network traffic but also causes high transmission delay. Mobile edge computing (MEC) is proposed to improve Quality of Service (QoS) for mobile applications in 5G networks. However, the data consistency for mobile applications still relies on replication schemes. Frequent updates may thus result in high communication overhead and long transmission latency. In this paper, we design an adaptive replication scheme for real-time mobile applications by considering the number of failed requests and the read/write request ratios. The simulation results show that our scheme can reduce the response time of data transmission to increase QoS performance.
12:15 Utilizing 2100 MHz for 4G LTE-A Network Deployment to Addressing Spectrum Scarcity in Urban Area
The current rapid growth of technology causes a tremendous increase in users adopting the latest technology, particularly in a large population country such as Indonesia. This increase in users then led to far more enormous network traffic congestion. One plausible solution to face this obstacle query in Indonesia is by adding a supplementary 4G LTE-Advanced network frequency. This study aims to use 2100 MHz frequency to implement a simulation of both capacity and coverage analysis of 4G LTE-Advanced network in North Jakarta, Indonesia. Afterward, this study provides the evaluations of Key Performance Indicators (KPI), Reference Signal Receive Power (RSRP), Signal to Interference Noise Ratio (SINR), radio bearer, and throughput analysis based on the obtained simulation results. This study obtained that the site number demanded for North Jakarta is 189 sites. Furthermore, the average RSRP, SINR, radio bearer, and throughput were -68.73 dBm, 4.1 dB, CQI Index 6, and 16.72 Mbps, respectively. These values met the requirements for the 2100 MHz frequency implementation in North Jakarta.
12:30 Intelligent Augmented Video Streaming Services Using Lightweight QR Code Scanner
Video streaming is a multimedia service that continuously transmits the data over the Internet and presents the content on user screens without predownloading the entire video. Augmented video streaming is an advanced version of video streaming, where the video is enriched with additional embedded information in video frames. These additional data aim to provide better user experience. In this context, using QR code is one of the efficient approaches to incorporate information into video streams. However, receiving the data in the embedded QR code is considered a challenging task owing to video quality and view angles. This paper proposes a lightweight two-stage QR code decoder for augmented video streaming using deep learning technologies. In the first stage, the position of the embedded QR code is detected using an online object detection algorithm. In the second stage, the detected region of the QR code is fed into a QR code reader to extract the embedded data. The experimental results show that the proposed decoder achieves high performances in terms of response time and decoding accuracy while being very lightweight, which is promising to be implemented in smartphones.
12:45 Multi-Device Task Offloading with Scheduling in an Edge Cloud Platform
Offloading is the way we manage jobs in mobile computing. We execute some jobs in the mobile device itself, cloud, or fog server in remote areas with more computing capability through the internet. Many researchers focus on minimizing mobile energy consumption by profiling the jobs, choosing the right combination of mobile-cloud execution. Little researchers focus on scheduling the job execution. In contrast, this execution schedule determines overall energy consumption and execution time of all mobile devices in a group of offloading, such as healthcare and security systems. Here, we propose a scheduled data transfer and job execution to minimize energy consumption and offloading time. Also, the scheduled offloading is compared to unscheduled ones in a cloud-edge platform. We get a significant time efficiency of 54 percent and -0,32 percent efficiency of energy from the simulation.
11:30 LoRaWAN Planning and Implementation Analysis for Smart Factories in Industrial Estates
LoRa could not directly connect to the server, so it requires a connecting device between the end node and the server, namely gateway. The purpose of network planning in this study is to estimate the number of LoRa gateways that can use as a guide in network implementation in the Industrial area of Kota Jababeka. The scenario used is Outdoor, Downlink communication with SF12 and a sensitivity level of Rx -137 dBm. Network planning method used capacity with an estimated number of IoT device subscribers in Kota Jababeka as much as 1,776,462 units and coverage analysis with MAPL Downlink value of 164 dB and calculations for radio network planning simulation. The implemented LoRa frequency of 920 MHz obtains eighth gateways. The parameters used to test the scenario are RSRP, SINR and Throughput. The RSRP value obtained has an average of -69.03 dBm and the standard deviation obtained is 8.22 dBm. The SINR value obtained has a mean of 20.15 dB which the standard deviation obtained is 19.92 dB. Both of these parameters included in the level good category. Finally, the average throughput distribution has 0.02 kbps.
11:45 Concatenated Coset Coding in a Multi-tone DHA FH OFDMA System with Order Statistics-based Reception
A coded modulation scheme for a single-band multi-tone DHA FH OFDMA system that employs order statistics-based reception and a concatenation of coset codes is proposed. It is demonstrated that this coded modulation scheme provides profound performance gain over the conventional coded single-band multi-tone DHA FH OFDMA while preserving the effective transmission rate at the expense of minor complexity increase.
12:00 Evaluation of Low-density parity-check code with 16-QAM OFDM in a time-varying channel
In wireless networks, multipath interference in a time-varying channel is a significant and major challenge to effective data transmission. Bit error rate (BER) efficiency is improved using Forward Error Correction (FEC) coding, such as Low-Density Parity-Check (LDPC) coding. LDPC, which can accomplish near Shannon limit efficiency and has recently gained considerable attention because of these properties. The efficiency of an LDPC coded orthogonal frequency division multiplexing (OFDM) communication scheme for time-varying channels is evaluated in this paper. Then we study the bandwidth-efficient coded modulation system based on LDPC codes that have low implementation complexity and high BER efficiency. Simulation is used to investigate the effects of modulation and coding schemes on the performance of the LDPC code. The results show that the device can significantly boost the efficiency of wireless channels while lowering the code rate and improving overall system performance.
12:15 Analysis of GFDM-OQAM Performance Using Zero Forcing Equalization
The demand for higher data rates and lower latency is driving the rapid development of cellular and communication system. GFDM is the successor to the communication system for the waveforms of future cellular networks. GFDM is a block-based multi-carrier technique where each subcarrier is formed with a non-rectangular pulse-shaped filter increase the location of the pulse frequency called pulse shaping. Offset-QAM Modulation (OQAM) can achieve better spectral efficiency. In this research, the equalization used is in the form of Zero forcing (ZF) equalization to detect the original signal sent by the sender. The result of this research indicated that the GFDM OQAM system using Zero Forcing equalization has a better BER value than the GFDM OQAM system. The GFDM OQAM without ZF obtained BER value of 0.1675 at 0 dB SNR and 0.05854 at 15 SNR. While the BER value on GFDM OQAM with ZF decreased BER from 0.1989 at 0 dB SNR to 0.0272 at 15 dB SNR, then the greater the Roll-off-factor value used, the higher the BER value.
12:30 Performance Analysis GFDM Using MMSE Equalization in Audio Transmission
To improve the performance of communication channels in the future Generalized Frequency Division Multiplexing (GFDM) becomes a new method used to update the Filter Bank Multicarrier (FBMC) and Orthogonal Frequency Division Multiplexing (OFDM) methods. In this research, equalization used Minimum Mean Square Error (MMSE). The performance of this research was measured by the parameters of comparing the ratio of signal strength to noise (SNR) to bit error rate (BER) and channel capacity. The results of this research resulted in BER value obtained in GFDM QAM without MMSE in SNR 0 dB obtained a BER value of 0.413. Then at the SNR value of 25 dB get a value of 0.1645. Meanwhile, in GFDM system with MMSE in SNR 0 dB get BER value of 0.4799. Then, on SNR 25 dB get a BER value of 0.0184. GFDM QAM system with MMSE produces better value than GFDM QAM system without MMSE. In roll off factor system testing when SNR 25 dB on roll off factor 1 has a BER value of 0.5009, for roll off factor 0.5 has a BER value of 0.02417. While in roll off factor 0.3 has a value of BER 0.02356. The greater the roll off factor value is higher BER value.
12:45 Minimizing the additional costs due to Router Outage in IP-over-EON using Adaptive Routing
When a router fails in IP-over-EON, some traffics are affected. Each affected traffic attempts to be restored through the best alternate path among alternate paths offered. Some conventional routing schemes are commonly used to solve problems in IP over optical networks, namely k-shortest paths (KSP), hop count (HC), and link-disjoint (LD). The three schemes are fixed-alternate routing (FAR) schemes. However, the alternate paths it generates cannot adjust to the current network conditions due to a router outage. Therefore, this study proposes an adaptive routing, i.e., adaptive lightpath reconfiguration paths (ALRP) routing. ALRP routing explores the number of paths between the source and destination pairs for each affected traffic and then selects the best alternate paths by maximizing the utilization of unaffected lightpaths. The goal is to minimize costs relate to the number of lightpath reconfiguration and additional power consumption due to the recovery of affected traffic. Based on simulations conducted using two network topologies, namely seven-node topology and NSFNET topology, it was found that the proposed ALRP routing produced better results compared to the three conventional routing schemes in minimizing the addition of both costs.