Akraino API TSC Ike Alisson 5G Mobility Edge MEC synergy present 2020 11 06 R...Ike Alisson
Edge in 5G Mobility context evolvement from NGMN 5G WP in Feb 2015 and ETSI MEC renaming MEC to Multi-access Edge Computing by March 2017 and setting Phase 2 New Scope with some examples from 3GPP Rel 15 NSA New Services and System Aspects enhancements revisiosn preceding ETSI MEC renaming and latest 5G Capabilities for Traffic Routing & Service Steering impact on MEC and latest support for AVT (Alternative Virtualized Technologies) and 5G SCEF/NEF SCS/AS for CIoT integrated (like in 5G MEC case through CAPIF/NAPS) with 5G SL IoT Platform oneM2M with support to Ontology SAREF across 10 UCs.
Akraino API TSC Ike Alisson 5G Mobility Edge MEC synergy present 2020 11 06 R...Ike Alisson
Edge in 5G Mobility context evolvement from NGMN 5G WP in Feb 2015 and ETSI MEC renaming MEC to Multi-access Edge Computing by March 2017 and setting Phase 2 New Scope with some examples from 3GPP Rel 15 NSA New Services and System Aspects enhancements revisiosn preceding ETSI MEC renaming and latest 5G Capabilities for Traffic Routing & Service Steering impact on MEC and latest support for AVT (Alternative Virtualized Technologies) and 5G SCEF/NEF SCS/AS for CIoT integrated (like in 5G MEC case through CAPIF/NAPS) with 5G SL IoT Platform oneM2M with support to Ontology SAREF across 10 UCs.
Mobility Management For Next Generation NetworksGreen Packet
Increasingly, operators worldwide will be faced with a similar challenge of managing data congestion over multiple access networks. With networks evolving into LTE, operators would need to carefully assess the technology fit into integrating complementary nature of multiple access networks into an all-IP flat architecture. An all IP flat architecture helps to tie heterogeneous access networks that devices can attach to access end-user services. Communication devices today are able to connect with more than one type of wireless technologies to the “web of things”. An end-user will connect to a Wi-Fi hotspot, if within range. When moving away from range, the communication link is handover to for example, UMTS. The motivation of inter-working lies in marrying the diverse strengths of each communication technology. High-bandwidth data communication inherent in WLAN lacks mobility. Conversely, cellular technologies such as UMTS succeed in highly mobile environments, but limited in bandwidth. Although cellular networks are evolving from today’s 3G to LTE that brings promise of capacity leaps (by nearly 4 times), the overall data growth projection will outpace LTE deployments and fill up very quickly.
The immediate need to curtail congested network and effectively manage mobility is imminent to accommodate the data traffic on their networks. The impact of inter-mobility between inter access technology together with various types of mobility support including 3GPP legacy network and non 3GPP is necessary to provide a target low-latency, higher data-rate, all-IP core network capable of supporting real-time packet services. Some of the available IP mobility protocols lack sufficient control to the network to optimize the handover process and do not handle well with slow connection setups of some wireless technologies. This paper highlights the potential approaches of bringing together mobility technologies that are available and how these approaches contribute to resolve operator concerns in deployment of services and combating congestion, access technology integration and evolution to LTE from legacy 3GPP networks.
COMPARATIVE AND QOS PERFORMANCE ANALYSIS OF TERRESTRIAL-AERIAL PLATFORMS-SATE...IJCNCJournal
Wireless communications, nowadays, becomes a vital element of people’s daily life. Providing global connectivity in future communication systems via the heterogeneous network opens up many research topics to investigate potentialities, enabling technologies, and challenges from the perspective of the
integrated wireless systems. This paper aims to drive a comprehensive and comparative study on terrestrial-aerial platforms- satellite wireless communications systems, includes their characteristics and unravelling challenges. The comparison focuses on issues that reportedly can evaluate any wireless
systems for temporary events. These issues are altitude and coverage, Radio Frequency (RF) propagation, interference, handover, power supply constraints, deployment and maintenance challenges, reliability on special events or disaster relief, cost-effectiveness and environmental impact. Last, Quality of service (QoS) performance is analysed for the four wireless communication systems from the temporary events
perspective using the OPNET Modeller simulation tool. Results infer that space-based wireless systems outperform terrestrial ones.
The relay stations are widely used in major wireless technologies such as WiMAX (Worldwide Interoperability for Microwave Access) and LTE (Long term evolution) which provide cost effective service to the operators and end users. It is quite challenging to provide guaranteed Quality of Service (QoS) in WiMAX networks in cost effective manner.
Optimization of Quality of Service in 4G Wireless NetworksIDES Editor
4G radio access technologies should be able to
provide different types of IP services. These services rang from
narrow-band to broadband, from non-real-time to real-time,
and from unicast to multicast broadcast applications. When
the need arises for different levels of user mobility the access
systems are required with advanced capabilities of radio
resource management and Quality of Service (QoS). We
present, in this paper, the different QoS approaches by the
various wireless and connectivity’s networks as well as the
issues that will face their implementations in 4G.
Mobile technology g, e, 3 g, 3g +, h, h + or 4g _4g bd _ third and fourth gen...www.4g-bd.com
Those who use a smartphone ( especially those who do it for the first time ) at some time have wondered who those letters ( G, E, 3G, 3G +, H, H + or 4G ) displayed next to the time in top, which also shows other information such as call coverage, time, battery, etc ...
http://www.4g-bd.com/2014/09/mobile-technology-g-e-3g-h-4g.html#sthash.kDJLtxcq.dpbs
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applicat...graphhoc
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes or terminals with
wireless communications and networking capability that communicate with each other without the aid of
any centralized administrator also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it’s an autonomous system in
which mobile hosts connected by wireless links are free to be dynamically and some time act as routers at
the same time, and we discuss in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time , there is no direction or limit the movement and
so on, and thus needed a new optional path Agreement (Routing Protocol) to identify nodes for these
actions communicate with each other path, An ideal choice way the agreement should not only be able to
find the right path, and the Ad Hoc Network must be able to adapt to changing network of this type at any
time. and we talk in details in this paper all the information of Mobile Ad Hoc Network which include the
History of ad hoc, wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc networks, and
then we present more than 13 types of the routing Ad Hoc Networks protocols have been proposed. In this
paper, the more representative of routing protocols, analysis of individual characteristics and advantages
and disadvantages to collate and compare, and present the all applications or the Possible Service of Ad
Hoc Networks
Security system with RFID control using E-KTP and internet of thingsjournalBEEI
Crimes against property without using violence, in this case, are theft and burglary is the type of crime that is most common every year. However, home security needs a security system that is more efficient and practical. To overcome this, an internet of things (IoT) is needed. This research evaluated the performance prototype by reading distance from the radio frequency identification (RFID) reader using E-KTP and quality of service performance (i.e throughput and delay) from application android. This research design smart door lock using RFID sensor, passive infrared sensor (PIR), solenoid as door locks, buzzer, led, E-KTP as RFID tags and also android application to controlling and monitoring made with android studio is connected to NodeMCU V3 ESP8266 as storage data and connect with firebase realtime database instead of conventional keys. This research focuses on performance prototype and quality of service from features application is work well. Related to previous works, our evaluation shows that the performance prototype can read identity card (E-KTP) with a maximum distance is 4 cm, and performance quality of service for an application show that throughput and delay with a perfect index according to standardization telecommunications and internet protocol harmonization over network (TIPHON) depending on what features are being evaluated.
5G uplink interference simulations, analysis and solutions: The case of pico ...IJECEIAES
The launch of the new mobile network technology has paved the way for advanced and more productive industrial applications based on high-speed and low latency services offered by 5G. One of the key success points of the 5G network is the available diversity of cell deployment modes and the flexibility in radio resources allocation based on user’s needs. The concept of Pico cells will become the future of 5G as they increase the capacity and improve the network coverage at a low deployment cost. In addition, the short-range wireless transmission of this type of cells uses little energy and will allow dense applications for the internet of things. In this contribution, we present the advantages of using Pico cells and the characteristics of this type of cells in 5G networks. Then, we will do a simulation study of the interferences impact in uplink transmission in the case of PICO cells densified deployment. Finally, we will propose a solution for interference avoidance between pico cells that also allows flexible management of bands allocated to the users in uplink according to user’s density and bandwidth demand.
Fifth generation (5G) Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies to
fulfill the requirements of modern services. Multiple services with dierent Quality of Service (QoS) constraints could be available in each vehicle, while at the same time, user requirements and provider policies must be addressed. Therefore, the design of ecient Vertical Handover (VHO) management schemes for 5G-VCC infrastructures is needed. In this paper, a novel VHO management scheme for 5G-VCC systems is proposed. Whenever the user satisfaction grade becomes less than a predefined threshold, VHO is initiated and network selection is performed, considering the velocity of the vehicle, network characteristic criteria such as throughput, delay, jitter and packet loss, as well as provider policy criteria such as service reliability, security and price. The proposed scheme uses linguistic values for VHO criteria attributes represented by Interval Valued Pentagonal Fuzzy Numbers (IVPFNs) to express the information using membership intervals. The VHO scheme is applied to a 5G-VCC system which includes 3GPP Long Term Evolution (LTE) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX) Macrocells and Femtocells, as well as IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs). Performance evaluation shows that the suggested method ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
Long term evolution (LTE) is replacing the 3G services slowly but steadily and become a preferred choice
for data for human to human (H2H) services and now it is becoming preferred choice for voice also. In
some developed countries the traditional 2G services gradually decommissioned from the service and
getting replaced with LTE for all H2H services. LTE provided high downlink and uplink bandwidth
capacity and is one of the technology like mobile ad hoc network (MANET) and vehicular ad hoc network
(VANET) being used as the backbone communication infrastructure for vehicle networking applications.
When Compared to VANET and MANET, LTE provides wide area of coverage and excellent infrastructure
facilities for vehicle networking. This helps in transmitting the vehicle information to the operator and
downloading certain information into the vehicle nodes (VNs) from the operators server. As per the ETSI
publications the number of machine to machine communication (MTC) devices are expected to touch 50
billion by 2020 and this will surpass H2H communication. With growing congestion in the LTE network,
accessing the network for any request from VN especially during peak hour is a big challenge because of
the congestion in random access channel (RACH). In this paper we will analyse this RACH congestion
problem with the data from the live network. Lot of algorithms are proposed for resolving the RACH
congestion on the basis of simulation results so we would like to present some practical data from the live
network to this issue to understand the extent RACH congestion issue in the real time scenario.
Mobility Management For Next Generation NetworksGreen Packet
Increasingly, operators worldwide will be faced with a similar challenge of managing data congestion over multiple access networks. With networks evolving into LTE, operators would need to carefully assess the technology fit into integrating complementary nature of multiple access networks into an all-IP flat architecture. An all IP flat architecture helps to tie heterogeneous access networks that devices can attach to access end-user services. Communication devices today are able to connect with more than one type of wireless technologies to the “web of things”. An end-user will connect to a Wi-Fi hotspot, if within range. When moving away from range, the communication link is handover to for example, UMTS. The motivation of inter-working lies in marrying the diverse strengths of each communication technology. High-bandwidth data communication inherent in WLAN lacks mobility. Conversely, cellular technologies such as UMTS succeed in highly mobile environments, but limited in bandwidth. Although cellular networks are evolving from today’s 3G to LTE that brings promise of capacity leaps (by nearly 4 times), the overall data growth projection will outpace LTE deployments and fill up very quickly.
The immediate need to curtail congested network and effectively manage mobility is imminent to accommodate the data traffic on their networks. The impact of inter-mobility between inter access technology together with various types of mobility support including 3GPP legacy network and non 3GPP is necessary to provide a target low-latency, higher data-rate, all-IP core network capable of supporting real-time packet services. Some of the available IP mobility protocols lack sufficient control to the network to optimize the handover process and do not handle well with slow connection setups of some wireless technologies. This paper highlights the potential approaches of bringing together mobility technologies that are available and how these approaches contribute to resolve operator concerns in deployment of services and combating congestion, access technology integration and evolution to LTE from legacy 3GPP networks.
COMPARATIVE AND QOS PERFORMANCE ANALYSIS OF TERRESTRIAL-AERIAL PLATFORMS-SATE...IJCNCJournal
Wireless communications, nowadays, becomes a vital element of people’s daily life. Providing global connectivity in future communication systems via the heterogeneous network opens up many research topics to investigate potentialities, enabling technologies, and challenges from the perspective of the
integrated wireless systems. This paper aims to drive a comprehensive and comparative study on terrestrial-aerial platforms- satellite wireless communications systems, includes their characteristics and unravelling challenges. The comparison focuses on issues that reportedly can evaluate any wireless
systems for temporary events. These issues are altitude and coverage, Radio Frequency (RF) propagation, interference, handover, power supply constraints, deployment and maintenance challenges, reliability on special events or disaster relief, cost-effectiveness and environmental impact. Last, Quality of service (QoS) performance is analysed for the four wireless communication systems from the temporary events
perspective using the OPNET Modeller simulation tool. Results infer that space-based wireless systems outperform terrestrial ones.
The relay stations are widely used in major wireless technologies such as WiMAX (Worldwide Interoperability for Microwave Access) and LTE (Long term evolution) which provide cost effective service to the operators and end users. It is quite challenging to provide guaranteed Quality of Service (QoS) in WiMAX networks in cost effective manner.
Optimization of Quality of Service in 4G Wireless NetworksIDES Editor
4G radio access technologies should be able to
provide different types of IP services. These services rang from
narrow-band to broadband, from non-real-time to real-time,
and from unicast to multicast broadcast applications. When
the need arises for different levels of user mobility the access
systems are required with advanced capabilities of radio
resource management and Quality of Service (QoS). We
present, in this paper, the different QoS approaches by the
various wireless and connectivity’s networks as well as the
issues that will face their implementations in 4G.
Mobile technology g, e, 3 g, 3g +, h, h + or 4g _4g bd _ third and fourth gen...www.4g-bd.com
Those who use a smartphone ( especially those who do it for the first time ) at some time have wondered who those letters ( G, E, 3G, 3G +, H, H + or 4G ) displayed next to the time in top, which also shows other information such as call coverage, time, battery, etc ...
http://www.4g-bd.com/2014/09/mobile-technology-g-e-3g-h-4g.html#sthash.kDJLtxcq.dpbs
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applicat...graphhoc
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes or terminals with
wireless communications and networking capability that communicate with each other without the aid of
any centralized administrator also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it’s an autonomous system in
which mobile hosts connected by wireless links are free to be dynamically and some time act as routers at
the same time, and we discuss in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time , there is no direction or limit the movement and
so on, and thus needed a new optional path Agreement (Routing Protocol) to identify nodes for these
actions communicate with each other path, An ideal choice way the agreement should not only be able to
find the right path, and the Ad Hoc Network must be able to adapt to changing network of this type at any
time. and we talk in details in this paper all the information of Mobile Ad Hoc Network which include the
History of ad hoc, wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc networks, and
then we present more than 13 types of the routing Ad Hoc Networks protocols have been proposed. In this
paper, the more representative of routing protocols, analysis of individual characteristics and advantages
and disadvantages to collate and compare, and present the all applications or the Possible Service of Ad
Hoc Networks
Security system with RFID control using E-KTP and internet of thingsjournalBEEI
Crimes against property without using violence, in this case, are theft and burglary is the type of crime that is most common every year. However, home security needs a security system that is more efficient and practical. To overcome this, an internet of things (IoT) is needed. This research evaluated the performance prototype by reading distance from the radio frequency identification (RFID) reader using E-KTP and quality of service performance (i.e throughput and delay) from application android. This research design smart door lock using RFID sensor, passive infrared sensor (PIR), solenoid as door locks, buzzer, led, E-KTP as RFID tags and also android application to controlling and monitoring made with android studio is connected to NodeMCU V3 ESP8266 as storage data and connect with firebase realtime database instead of conventional keys. This research focuses on performance prototype and quality of service from features application is work well. Related to previous works, our evaluation shows that the performance prototype can read identity card (E-KTP) with a maximum distance is 4 cm, and performance quality of service for an application show that throughput and delay with a perfect index according to standardization telecommunications and internet protocol harmonization over network (TIPHON) depending on what features are being evaluated.
5G uplink interference simulations, analysis and solutions: The case of pico ...IJECEIAES
The launch of the new mobile network technology has paved the way for advanced and more productive industrial applications based on high-speed and low latency services offered by 5G. One of the key success points of the 5G network is the available diversity of cell deployment modes and the flexibility in radio resources allocation based on user’s needs. The concept of Pico cells will become the future of 5G as they increase the capacity and improve the network coverage at a low deployment cost. In addition, the short-range wireless transmission of this type of cells uses little energy and will allow dense applications for the internet of things. In this contribution, we present the advantages of using Pico cells and the characteristics of this type of cells in 5G networks. Then, we will do a simulation study of the interferences impact in uplink transmission in the case of PICO cells densified deployment. Finally, we will propose a solution for interference avoidance between pico cells that also allows flexible management of bands allocated to the users in uplink according to user’s density and bandwidth demand.
Fifth generation (5G) Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies to
fulfill the requirements of modern services. Multiple services with dierent Quality of Service (QoS) constraints could be available in each vehicle, while at the same time, user requirements and provider policies must be addressed. Therefore, the design of ecient Vertical Handover (VHO) management schemes for 5G-VCC infrastructures is needed. In this paper, a novel VHO management scheme for 5G-VCC systems is proposed. Whenever the user satisfaction grade becomes less than a predefined threshold, VHO is initiated and network selection is performed, considering the velocity of the vehicle, network characteristic criteria such as throughput, delay, jitter and packet loss, as well as provider policy criteria such as service reliability, security and price. The proposed scheme uses linguistic values for VHO criteria attributes represented by Interval Valued Pentagonal Fuzzy Numbers (IVPFNs) to express the information using membership intervals. The VHO scheme is applied to a 5G-VCC system which includes 3GPP Long Term Evolution (LTE) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX) Macrocells and Femtocells, as well as IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs). Performance evaluation shows that the suggested method ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
Long term evolution (LTE) is replacing the 3G services slowly but steadily and become a preferred choice
for data for human to human (H2H) services and now it is becoming preferred choice for voice also. In
some developed countries the traditional 2G services gradually decommissioned from the service and
getting replaced with LTE for all H2H services. LTE provided high downlink and uplink bandwidth
capacity and is one of the technology like mobile ad hoc network (MANET) and vehicular ad hoc network
(VANET) being used as the backbone communication infrastructure for vehicle networking applications.
When Compared to VANET and MANET, LTE provides wide area of coverage and excellent infrastructure
facilities for vehicle networking. This helps in transmitting the vehicle information to the operator and
downloading certain information into the vehicle nodes (VNs) from the operators server. As per the ETSI
publications the number of machine to machine communication (MTC) devices are expected to touch 50
billion by 2020 and this will surpass H2H communication. With growing congestion in the LTE network,
accessing the network for any request from VN especially during peak hour is a big challenge because of
the congestion in random access channel (RACH). In this paper we will analyse this RACH congestion
problem with the data from the live network. Lot of algorithms are proposed for resolving the RACH
congestion on the basis of simulation results so we would like to present some practical data from the live
network to this issue to understand the extent RACH congestion issue in the real time scenario.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Today wireless services are the most preferred services of the world. The rapid increase in
the service is due to the advancement of technology consecutively. As a subscriber becomes more
aware of the mobile phone technology, he/she will seek for an appropriate package all together, and
including all the advanced features of a cellular phone can have. Hence, the search for new
technology is always the main intention of the prime cell phone giants to out innovate their
competitors. In addition, the main purpose of the fifth generation wireless networks (5G Wireless
networks) is planned to design the best wireless world that is free from limitations and hindrance of
the previous generations. 5G technologies will change the way most high bandwidth users access
their Mobile Radio Communication (MRC). So, this paper represents, great evolution of 1G (First
Generation) to 4G yield 5G, introduction to 5G technologies, why there is a need for 5G, advantages
of 5G networks technology, exceptional applications, Quality of Service (QoS), 5G network
architecture.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
A Comparative Study on 4G and 5G Technology for Wireless Applicationsiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Correlation between Terms of 5G Networks, IoT and D2D Communicationijtsrd
The proliferation of heterogeneous devices connected through large scale networks is a clear sign that the vision of the Internet of Things IoT is getting closer to becoming a reality. Many researchers and experts in the field share the opinion that the next to come fifth generation 5G cellular systems will be a strong boost for the IoT deployment. Device to Device D2D appears as a key communication paradigm to support heterogeneous objects interconnection and to guarantee important benefits. Future research directions are then presented towards a fully converged 5G IoT ecosystem. In this paper, we analyze existing data about D2D communication systems and its relation of 5G IoT networks. The enhancement of such networks will bring several spheres to learn for. Nozima Musaboyeva Bahtiyor Qizi "Correlation between Terms of 5G Networks, IoT and D2D Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-6 , October 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47522.pdf Paper URL : https://www.ijtsrd.com/computer-science/computer-network/47522/correlation-between-terms-of-5g-networks-iot-and-d2d-communication/nozima-musaboyeva-bahtiyor-qizi
A FUTURE MOBILE PACKET CORE NETWORK BASED ON IP-IN-IP PROTOCOLIJCNCJournal
The current Evolved Packet Core (EPC) 4th generation (4G) mobile network architecture features complicated control plane protocols and requires expensive equipment. Data delivery in the mobile packet core is performed based on a centralized mobility anchor between eNode B (eNB) elements and the network gateways. The mobility anchor is performed based on General Packet Radio Service tunnelling protocol (GTP), which has numerous drawbacks, including high tunnelling overhead and suboptimal routing between mobile devices on the same network. To address these challenges, here we describe new mobile core architecture for future mobile networks. The proposed scheme is based on IP encapsulated within IP (IP-in-IP) for mobility management and data delivery. In this scheme, the core network functions via layer 3 switching (L3S), and data delivery is implemented based on IP-in-IP routing, thus eliminating the GTP tunnelling protocol. For handover between eNB elements located near to one another, we propose the creation of a tunnel that maintains data delivery to mobile devices until the new eNB element updates the route with the gateway, which prevents data packet loss during handover. For this, we propose Generic Routing Encapsulation (GRE) tunnelling protocol. We describe the results of numerical analyses and simulation results showing that the proposed network core architecture provides superior performance compared with the current 4G architecture in terms of handover delay, tunnelling overhead and total transmission delay.
Data Communication in Internet of Things: Vision, Challenges and Future Direc...TELKOMNIKA JOURNAL
Ubiquitous technologies based heterogeneous networks has opened a new paradigm of technologies, which are enabled with various different objects called Internet of things (IoT). This field opens new door for innovative and advance patterns with considerable potential advantages in the shape of plethora of monitoring and infotainment applications around us. Data communication is one of the significant area of research in IoT due to its diverse network topologies, where diverse gadgets and devices have integrated and connected with each other. In order to communicate among devices and users, routing should be relible, secure and efficient. Due to diverse and hetrogenous netwok environment, the most of the existing routing solutions do not provide all quality of services requirement in the network. In this paper, we discuss the existing routing trend in IoT, vision and current challenges. This paper also elaborates the technologies and domains to drive this field for future perspectives. The paper concludes with discussion and main points for new researchers in terms of routing to understand about current situation in IoT.
Towards Future 4G Mobile Networks: A Real-World IMS Testbedjosephjonse
In the near future, current mobile communication networks will converge towards an All-IP network in order to provide richer applications, stronger customer satisfaction, andfurther return on investment for the industry. However, such a convergence induces a strong level of complexity when handling interoperability between different operators and different handset vendors. In this context, the 3GPP consortium is working on the standardization of the convergence, and IMS is emerging as the internationally agreed upon standard that is multi-operator and multi-vendor. In this paper, we shed further light on the subtleties of IMS, and we delineate a blueprint for the implementation of a real-world IMS testbed. An open source Presence Server is deployed as well. The operation of the IMS testbed and the Presence Server are checked to assess their conformance with 3GPP standards. A simple third party application is developed on top the IMS testbed to further assess its operation.
TOWARDS FUTURE 4G MOBILE NETWORKS: A REAL-WORLD IMS TESTBEDijngnjournal
In the near future, current mobile communication networks will converge towards an All-IP network in order to provide richer applications, stronger customer satisfaction, andfurther return on investment for the industry. However, such a convergence induces a strong level of complexity when handling interoperability between different operators and different handset vendors. In this context, the 3GPP consortium is working on the standardization of the convergence, and IMS is emerging as the internationally agreed upon standard that is multi-operator and multi-vendor. In this paper, we shed further light on the subtleties of IMS, and we delineate a blueprint for the implementation of a real-world
IMS testbed. An open source Presence Server is deployed as well. The operation of the IMS testbed and the Presence Server are checked to assess their conformance with 3GPP standards. A simple third party application is developed on top the IMS testbed to further assess its operation.
An Efficient Mobile Gateway Selection and Discovery Based-Routing Protocol in...IJCNCJournal
Coupling cellular communication networks with vehicular ad hoc networks (VANET) can be a very interesting way out for providing Internet access to vehicles in the road. However, due to the several specific characteristics of VANETs, making an efficient multi-hop routing from vehicular sources to the Internet gateways through Long Term Evolution (LTE) technology is still challenging. In this paper, an Internet mobile gateway selection scheme is proposed to elect more potential vehicles to behave as gateways to Internet in VANETs. Therefore, the discovery and the selection of route to those mobiles gateways is carried out via an efficient multiple metrics-based relay selection mechanism. The objective is to select the more reliable route to the mobile gateways, by reducing the communication overhead and performing seamless handover. The proposed protocol is compared with one recent protocol based on packet delivery ratio, average end-to-end delay and overhead. The results show that the proposed protocol ameliorates significantly the network performance in the contrast of the other protocol.
AN EFFICIENT MOBILE GATEWAY SELECTION AND DISCOVERY BASED-ROUTING PROTOCOL IN...IJCNCJournal
Coupling cellular communication networks with vehicular ad hoc networks (VANET) can be a very
interesting way out for providing Internet access to vehicles in the road. However, due to the several
specific characteristics of VANETs, making an efficient multi-hop routing from vehicular sources to the
Internet gateways through Long Term Evolution (LTE) technology is still challenging. In this paper, an
Internet mobile gateway selection scheme is proposed to elect more potential vehicles to behave as
gateways to Internet in VANETs. Therefore, the discovery and the selection of route to those mobiles
gateways is carried out via an efficient multiple metrics-based relay selection mechanism. The objective is
to select the more reliable route to the mobile gateways, by reducing the communication overhead and
performing seamless handover. The proposed protocol is compared with one recent protocol based on
packet delivery ratio, average end-to-end delay and overhead. The results show that the proposed protocol
ameliorates significantly the network performance in the contrast of the other protocol.
Similar to Conference Paper: Distributed cloud and de-centralized control plane A proposal for scalable control plane for 5G (20)
Ericsson Technology Review: Versatile Video Coding explained – the future of ...Ericsson
Continuous innovation in 5G networks is creating new opportunities for video-enabled services for both consumers and industries, particularly in areas such as the Internet of Things and the automotive sector. These new services are expected to rely on continued video evolution toward 8K resolutions and beyond, and on new strict requirements such as low end-to-end latency for video delivery.
The latest Ericsson Technology Review article explores recent developments in video compression technology and introduces Versatile Video Coding (VVC) – a significant improvement on existing video codecs that we think deserves to be widely deployed in the market. VVC has the potential both to enhance the user experience for existing video services and offer an appropriate performance level for new media services over 5G networks.
BRIDGING THE GAP BETWEEN PHYSICAL AND DIGITAL REALITIES
The key role that connectivity plays in our personal and professional lives has never been more obvious than it is today. Thankfully, despite the sudden, dramatic changes in our behavior earlier this year, networks all around the world have proven to be highly resilient. At Ericsson, we’re committed to ensuring that the network platform continues to improve its ability to meet the full range of societal needs as well as supporting enterprises to stay competitive in the long term. We know that greater agility and speed will be essential.
This issue of our magazine includes several articles that explain Ericsson’s approach to future network development, including my annual technology trends article. The seven trends on this year’s list serve as a critical cornerstone in the development of a common Ericsson vision of what future networks will provide, and what sort of technology evolution will be required to get there.
ERIK EKUDDEN
Senior Vice President, Chief Technology Officer and Head of Group Function Technology
Ericsson Technology Review: Integrated access and backhaul – a new type of wi...Ericsson
Today millimeter wave (mmWave) spectrum is valued mainly because it can be used to achieve high speeds and capacities when combined with spectrum assets below 6GHz. But it can provide other benefits as well. For example, mmWave spectrum makes it possible to use a promising new wireless backhaul solution for 5G New Radio – integrated access and backhaul (IAB) – to densify networks with multi-band radio sites at street level.
This Ericsson Technology Review article explains the IAB concept at a high level, presenting its architecture and key characteristics, as well as examining its advantages and disadvantages compared with other backhaul technologies. It concludes with a presentation of the promising results of several simulations that tested IAB as a backhaul option for street sites in both urban and suburban areas.
Ericsson Technology Review: Critical IoT connectivity: Ideal for time-critica...Ericsson
Critical Internet of Things (IoT) connectivity is an emerging concept in IoT development that enables more efficient and innovative services across a wide range of industries by reliably meeting time-critical communication needs. Mobile network operators (MNOs) are in the perfect position to enable these types of time-critical services due to their ability to leverage advanced 5G networks in a systematic and cost-effective way.
This Ericsson Technology Review article explores the benefits of Critical IoT connectivity in areas such as industrial control, mobility automation, remote control and real-time media. It also provides an overview of key network technologies and architectures. It concludes with several case studies based on two deployment scenarios – wide area and local area – that illustrate how well suited 5G spectrum assets are for Critical IoT use cases.
5G New Radio has already evolved in important ways since the 3GPP standardized Release 15 in late 2018. The significant enhancements in Releases 16 and 17 are certain to play a critical role in expanding both the availability and the applicability of 5G NR in both industry and public services in the near future.
This Ericsson Technology Review article summarizes the most notable new developments in releases 16 and 17, grouped into two categories: enhancements to existing features and features that address new verticals and deployment scenarios. This analysis and our insights about the future beyond Release 17 is an important component of our work to help mobile network operators and other stakeholders better understand and plan for the many new 5G NR opportunities that are on the horizon.
Ericsson Technology Review: The future of cloud computing: Highly distributed...Ericsson
The growing interest in cloud computing scenarios that incorporate both distributed computing capabilities and heterogeneous hardware presents a significant opportunity for network operators. With a vast distributed system (the telco network) already in place, the telecom industry has a significant advantage in the transition toward distributed cloud computing.
This Ericsson Technology Review article explores the future of cloud computing from the perspective of network operators, examining how they can best manage the complexity of future cloud deployments and overcome the technical challenges. Redefining cloud to expose and optimize the use of heterogeneous resources is not straightforward, but we are confident that our use cases and proof points validate our approach and will gain traction both in the telecommunications community and beyond.
Ericsson Technology Review: Optimizing UICC modules for IoT applicationsEricsson
Commonly referred to as SIM cards, the universal integrated circuit cards (UICCs) used in all cellular devices today are in fact complex and powerful minicomputers capable of much more than most Internet of Things (IoT) applications require. Until a simpler and less costly alternative becomes available, action must be taken to ensure that the relatively high price of UICC modules does not hamper IoT growth.
This Ericsson Technology Review article presents two mid-term approaches. The first is to make use of techniques that reduce the complexity of using UICCs in IoT applications, while the second is to use the UICCs’ excess capacity for additional value generation. Those who wish to exploit the potential of the UICCs to better support IoT applications have the opportunity to use them as cryptographic storage, to run higher-layer protocol stacks and/or as supervisory entities, for example.
Mobile data traffic volumes are expected to increase by a factor of four by 2025, and 45 percent of that traffic will be carried by 5G networks. To deliver on customer expectations in this rapidly changing environment, communication service providers must overcome challenges in three key areas: building sufficient capacity, resolving operational inefficiencies through automation and artificial intelligence, and improving service differentiation. This issue of ETR magazine provides insights about how to tackle all three.
Ericsson Technology Review: 5G BSS: Evolving BSS to fit the 5G economyEricsson
The 5G network evolution has opened up an abundance of new business opportunities for communication service providers (CSPs) in verticals such as industrial automation, security, health care and automotive. In order to successfully capitalize on them, CSPs must have business support systems (BSS) that are evolved to manage complex value chains and support new business models. Optimized information models and a high degree of automation are required to handle huge numbers of devices through open interfaces.
This Ericsson Technology Review article explains how 5G-evolved BSS can help CSPs transform themselves from traditional network developers to service enablers for 5G and the Internet of Things, and ultimately to service creators with the ability to collaborate beyond telecoms and establish lucrative digital value systems.
Ericsson Technology Review: 5G migration strategy from EPS to 5G systemEricsson
For many operators, the introduction of the 5G System (5GS) to provide wide-area services in existing Evolved Packet System (EPS) deployments is a necessary step toward creating a full-service, future-proof 5GS in the longer term. The creation of a combined 4G-5G network requires careful planning and a holistic strategy, as the introduction of 5GS has significant impacts across all network domains, including the RAN, packet core, user data and policies, and services, as well as affecting devices and backend systems.
This Ericsson Technology Review article provides an overview of all the aspects that operators need to consider when putting together a robust EPS-to-5GS migration strategy and provides guidance about how they can adapt the transition to address their particular needs per domain.
Ericsson Technology Review: Creating the next-generation edge-cloud ecosystemEricsson
The surge in data volume that will come from the massive number of devices enabled by 5G has made edge computing more important than ever before. Beyond its abilities to reduce network traffic and improve user experience, edge computing will also play a critical role in enabling use cases for ultra-reliable low-latency communication in industrial manufacturing and a variety of other sectors.
This Ericsson Technology Review article explores the topic of how to deliver distributed edge computing solutions that can host different kinds of platforms and applications and provide a high level of flexibility for application developers. Rather than building a new application ecosystem and platform, we strongly recommend reusing industrialized and proven capabilities, utilizing the momentum created with Cloud Native Computing Foundation, and ensuring backward compatibility.
The rise of the innovation platform
Society and industry are transforming at an unprecedented rate. At the same time, the network platform is emerging as an innovation platform with the potential to offer all the connectivity, processing, storage and security needed by current and future applications. In my 2019 trends article, featured in this issue of Ericsson Technology Review, I share my view of the future network platform in relation to six key technology trends.
This issue of the magazine also addresses critical topics such as trust enablement, the extension of computing resources all the way to the edge of the mobile network, the growing impact of the cloud in the telco domain, overcoming latency and battery consumption challenges, and the need for end-to-end connectivity. I hope it provides you with valuable insights about how to overcome the challenges ahead and take full advantage of new opportunities.
Ericsson Technology Review: Spotlight on the Internet of ThingsEricsson
The Internet of Things (IoT) has emerged as a fundamental cornerstone in the digitalization of both industry and society as a whole. It represents a huge opportunity not only in economic terms, but also from a global challenges perspective – making it easier for governments, non-governmental organizations and the private sector to address pressing food, energy, water and climate related issues.
5G and the IoT are closely intertwined. One of the biggest innovations within 5G is support for the IoT in all its forms, both by addressing mission criticality as well as making it possible to connect low-cost, long-battery-life sensors.
With this in mind, we decided to create a special issue of Ericsson Technology Review solely focused on IoT opportunities and challenges. I hope it provides you with valuable insights about the IoT-related opportunities available to your organization, along with ideas about how we can overcome the challenges ahead.
Ericsson Technology Review: Driving transformation in the automotive and road...Ericsson
A variety of automotive and transport services that require cellular connectivity are already in commercial operation today, and many more are yet to come. Among other things, these services will improve road safety and traffic efficiency, saving lives and helping to reduce the emissions that contribute to climate change. At Ericsson, we believe that the best way to address the growing connectivity needs of this industry sector is through a common network solution, as opposed to taking a single-segment silo approach.
The latest Ericsson Technology Review article explains how the ongoing rollout of 5G provides a cost-efficient and feature-rich foundation for a horizontal multiservice network that can meet the connectivity needs of the automotive and transport ecosystem. It also outlines the key challenges and presents potential solutions.
This presentation explains the importance of SD-WAN technology as part of the Enterprise digital transformation strategy. It goes over the first wave of SD-WAN in a single vendor deployment, with Do-it-yourself (DIY) as the preferred model. Then continues with the importance of orchestration in the second wave of SD-WAN deployments in a multi-vendor ecosystem, turning to SD-WAN Managed Services as the preferred model. It ends up with some examples of use cases and the Verizon customer case. More information on Ericsson Dynamic orchestration - http://m.eric.sn/6rsZ30psKLu
Ericsson Technology Review: 5G-TSN integration meets networking requirements ...Ericsson
Time-Sensitive Networking (TSN) is becoming the standard Ethernet-based technology for converged networks of Industry 4.0. Understanding the importance and relevance of TSN features, as well as the capabilities that allow 5G to achieve wireless deterministic and time-sensitive communication, is essential to industrial automation in the future.
The latest Ericsson Technology Review article explains how TSN is an enabler of Industry 4.0, and that together with 5G URLLC capabilities, the two key technologies can be combined and integrated to provide deterministic connectivity end to end. It also discusses TSN standards and the value of the TSN toolbox for next generation industrial automation networks.
Ericsson Technology Review: Meeting 5G latency requirements with inactive stateEricsson
Low latency communication and minimal battery consumption are key requirements of many 5G and IoT use cases, including smart transport and critical control of remote devices. Thanks to Ericsson’s 4G/5G research activities and lessons learned from legacy networks, we have identified solutions that address both of these requirements by reducing the amount of signaling required during state transitions, and shared our discoveries with the 3GPP.
This Ericsson Technology Review article explains the why and how behind the new Radio Resource Control (RRC) state model in the standalone version of the 5G New Radio standard, which features a new, Ericsson-developed state called inactive. On top of overcoming latency and battery consumption challenges, the new state also increases overall system capacity by decreasing the processing effort in the network.
Ericsson Technology Review: Cloud-native application design in the telecom do...Ericsson
Cloud-native application design is set to become standard practice in the telecom industry in the near future due to the major efficiency gains it can provide, particularly in terms of speeding up software upgrades and releases. At Ericsson, we have been actively exploring the potential of cloud-native computing in the telecom industry since we joined the Cloud Native Computing Foundation (CNCF) a few years ago.
This Ericsson Technology Review article explains the opportunities that CNCF technology has enabled, as well as unveiling key aspects of our application development framework, which is designed to help navigate the transition to a cloud-native approach. It also discusses the challenges that the large-scale reuse of open-source technology can raise, along with key strategies for how to mitigate them.
Ericsson Technology Review: Service exposure: a critical capability in a 5G w...Ericsson
To meet the requirements of use cases in areas such as the Internet of Things, AR/VR, Industry 4.0 and the automotive sector, operators need to be able to provide computing resources across the whole telco domain – all the way to the edge of the mobile network. Service exposure and APIs will play a key role in creating solutions that are both effective and cost efficient.
The latest Ericsson Technology Review article explores recent advances in the service exposure area that have resulted from the move toward 5G and the adoption of cloud-native principles, as well as the combination of Service-based Architecture, microservices and container technologies. It includes examples that illustrate how service exposure can be deployed in a multitude of locations, each with a different set of requirements that drive modularity and configurability needs.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Conference Paper: Distributed cloud and de-centralized control plane A proposal for scalable control plane for 5G
1. Distributed cloud and de-centralized control plane
A proposal for scalable control plane for 5G
Amir Roozbeh
Ericsson Research, Cloud Technology
Stockholm, Sweden
Email: amir.roozbeh@ericsson.com
Abstract—5G is the next generation of mobile network.
The aim is to launch service starting in 2020. There are
many requirements on 5G, such as high capacity, low latency,
flexibility, and support for any-to-any communication. Cloud
technology, in the form of a distributed cloud (also known
as a network embedded cloud), is an enabler technology for
5G by providing flexible networks to meet different user
application requirements. On the other hand, Machine Type
Communication (MTC) is a primary application for 5G, but
it can add a high volume of control signaling. To manage the
expected high volume of control signaling introduced by MTC,
we identified the main control events that generate signaling
messages in the network, i.e., session management, hand over
management, and tracking area update. Then, we proposed
a decentralized core network architecture optimized for the
identified control events. The proposed control plane functions
are independent of each other in the sense that each function
can be executed separately. The control functions can utilize
a distributed cloud ( embedded in the 5G core network) to
manage the enormous amount of control signaling by handling
this signaling locally, i.e., close to the end user. Additionally, we
present an analysis of the control signaling performance for each
proposed control function. The result shows that it is beneficial
to move session management to data centers collocated with
the base station in the 5G network when there is high user density.
Keywords: 5G, decentralized control function, core network,
network enabled cloud
I. INTRODUCTION
Mobile communications have had a significant impact on
the way that people and devices interconnect. Historically
there has been an evolution of wireless technology in terms
of radio access technology, data rates, operational bandwidth,
and mobile network architecture every ten years [1].
First generation mobile communication aimed at connect-
ing people by combining communications and mobility in
one package utilizing a circuit switch network in 1980. The
(r)evolution in mobile communication began with adapting the
mobile architecture to support packet switch networking. This
lead to the second generation 2G (i.e., introduced in 1990s),
such as Global System for Mobil Communications (GSM),
and later 3rd generation (3G) mobile networks. 2G introduced
increased capacity and coverage, enabling additional services
beyond voice, such as SMS and Email. Later, 3G introduced
mobile broadband (i.e., up to 2 Mbps) by combining high-
speed mobile access with IP services. In recent years, wireless
technologies (r)evolution resulted in an all-IP architecture, i.e.,
fourth generation (4G) together with Long Term Evolution
Advanced (LTE Advanced). The term all-IP refers to the fact
that all data and signaling within the mobile network utilize
the Internet Protocol (IP) on the network layer.
Today there are wide ranges of requirements on the next
generation of mobile communication, i.e., fifth generation
(5G). These requirements include: higher data rates and in-
creased traffic capacity (i.e., 1000 time more capacity than 4G),
improved reliability, support for enormous numbers of devices,
and lower latency. As a result, 5G has to be more efficient and
scalable than 4G [2]. 5G is concerned not only with providing a
service for people but also serving any devices that may benefit
from being connected. In another word, the next generation of
mobile communication should enable anyone or anything to
access information and share data anywhere, anytime [3].
IOT is one of the important applications for 5G. In the
transition to a networked society and connected planet with
5G, a massive number of devices, which can be embedded
into the environment, will be connected to networks. The
concept of IOT combines different Machine-Type Commu-
nications (MTC) (i.e., Machine-to-Machine and Machine-to-
Human) with human communication (i.e., Human-to-Human
and Human-to-Machine). Wearable devices, smart homes,
smart parking places, smart and self-driving cars, and smart
sensors are some example applications of MTC. IOT devices
can be categorized based on many factors such as their
portability (i.e., fixed or mobile) or communication direction
(i.e., one-way or two-way communication). Most IOT devices
are characterized by their simplicity, the fact that they usually
transmit small amounts of data, and whether they transmit
frequent or only from time to time.
5G has a requirement to support hundreds of billions
of low-power connections in order to bring IOT to peoples
daily lives. The enormous number of IOT devices and IOT
application characteristics in a future communication ecosys-
tem will have an impact on future mobile communication
architectures. IOT and MTC will effect both the user plane
and control plane traffic that need to be handled by future 5G
networks. Management of billions of IOT devices is expected
to add considerable signaling loads on the control plane of
the network, but this may lead to higher response times and
increased congestion at network control plane entities. The
future 5G control plane should be designed to avoid congestion
and reduce latency of the control plane, while providing a
flexible framework which can adapt to user requirements in a
wide variety of different scenarios.
2. In this paper, we present a decentralized control plane
function for 5G to provide the scalability needed for IOT
control signaling traffic. In this proposal, the mobile network
control plane is divided into different functions based on the
primary control events expected in a mobile network. Each
of the proposed functions can execute in a decentralized or
centralized way, depending upon the network’s demands to
handle signaling traffic.
The reminder of this paper is organized as follows:
Section II presents an overview of LTE network and 5G
characteristics and concept. Section III describes the concept
of IOT and how this can effect signaling load. Section IV
gives a description of the proposed control plane architecture
for 5G. Section V gives an analytic model used to calculate
signaling load on different control plane functions in 5G.
Additionally, a numerical analysis is made based on the
analytic model and metrics from an LTE network as a
baseline of 5G. Finally, we conclude the paper in Section VII.
II. FIFTH GENERATION (5G)
The 5th generation of mobile network (5G) is in its early
stage and lack a standard architecture and protocol. As a result,
this paper uses Long Term Evolution (LTE) technology as a
baseline to identify the main control plane events that produce
signaling load. The assumption is that a future 5G architecture
will evolve from today’s All-IP LTE. In this section we provide
overview about the LTE network followed by a description of
the expected 5G characteristics and underlying concepts.
A. LTE NETWORK
The LTE network architecture separates the control plane
and user plane (or data plane) [4]. The control plane is respon-
sible for control and transmission of signaling information,
while the user plane is responsible for forwarding user traffic.
This flat architecture has two parts: the Evolved-Universal
Terrestrial Radio Access Network (E-UTRAN) and Evolved
Packet Core (EPC). E-UTRAN consists of evolved node-
BSs (eNodeBs) that are responsible for providing wireless
connectivity to the user entities (UEs). EPC consists of four
primary entities: Mobility Management Entity (MME), Home
Subscriber Server (HSS), Packet Data Network Gateway (P-
GW), and serving gateway (S-GW). EPC provides functions
for user plane and control signaling management. Fig. 1 shows
the LTE network architecture. The EPC also includes standard
component of IP networks, such as switches, DNS, and NTP
servers (although these are not shown in this figure).
An MME is a critical control node in the EPC and supports
the most important control plane functions, specifically mobil-
ity managements managing security when device attaches to
the access network, and tracking and paging to support devices
in idle mode. MME uses information provided by HSS to
authenticate devices and updates UE’s location information in
HSS as part of its mobility management.
HSS is a database that contains subscriber-related informa-
tion. HSS provides support functions related to call and session
setup, user authentication, access authorization, and mobility
management.
The P-GW and S-GW of the core network act as a gateway
for user plane. These two elements provide connectivity
Fig. 1. LTE architecture.
between the UE and external IP networks. The S-GW is
logically connected to a P-GW and provides the intercon-
necting between the radio access network and EPC. The P-
GW interconnects the EPC with external IP networks. The P-
GW offers several functions, such as IP address management,
policy control, and charging.
LTE network elements communicate with each other by us-
ing standard interfaces defined by the 3rd Generation Partner-
ship Project (3GPP). For example, eNodeBs are interconnected
with each other by means of the X2 interface [5], while S10
is the standard interface between two MMEs. There are four
main events that initiate signaling control in LTE network:
a UE-originated session, a UE-terminated session, Handover
(HO), and Tracking Area Update (TAU).
A UE-originated session occurs when a UE attempts to
establish a connection to the EPC in order to receive or
send data. The signaling messages involved in this procedure
are shown in Fig. 2. To initiate the communication link, UE
starts the Radio Resource Control (RRC) connection procedure
with an eNodeB to ask for resources from access network,
(in step 1). In step 2, the UE sends an ATTACH and PDN
CONNECTIVITY request to MME to set up an internet
connection (this is referred to as a Non-Access Stratum (NAS)
service). If the MME is unable to identify the user (for example
because the UE has just at powered on or at the time initial
access to the network), then the MME starts identification and
authorization as NAS common procedure (in step 3). This
process involves six messages between the UE and MME. The
MME updates the HSS with the UE’s location while asking for
this subscriber’s profile. Also, there is a negotiation between
MME and S-GW and P-GW to establish an initial bearer for
this UE (in steps 4 - 7). Next the MME sends a context setup
request to the eNodeB that results in a signaling message being
sent between the eNodeB and UE to establish a bearer between
these two entities (in steps 8 - 10). When the initial context
configuration is satisfactory, the MME configure the user plane
of S-GW and sends an ‘attach accept” to UE (in steps 11 -
15 ). At this point, the data flow between the UE and external
network is established. Finally, when the session is complete
the MME can release all bearers allocated for this session (in
steps 16 - 21).
A UE-terminated session occurs when the network has data
for an idle UE. In this situation, the MME starts by paging all
3. Fig. 2. UE-originated session signaling message flow.
eNodeBs (within a tracking area size that UE registered with
it) in order to notify the UE that there is pending data for it.
The remainder of the procedure is same as for UE-originated
session, as shown in Fig. 3.
Handover (HO) can occur when the UE is idle or in
connected mode. We ignore those cases when HO occurs
when UE is in idle mode or when a HO occurs within a
single eNodeB (i.e., when a UE changes its cell sector),
as in both of these cases the MME is not involved in the
signaling procedure [6]. During a HO the UE may stay with
a given MME (i.e., an intra-MME HO) or need to change
its MME (i.e., an inter-MME HO). Intra-MME HO occurs
when an MME serves multiple eNodeBs. In this scenario, a
UE can continue to use its S-GW (i.e., intra-MME/SGW HO)
or changes its S-GW (i.e., intra-MME/inter-SGW HO). The
source eNodeB (SeNB) triggers a HO based on measurements
reported by a UE. A summary of intra-MME/SGW HO
signaling flows and a description of this HO procedure is
depicted in Fig. 4. These scenarios assume that the a X2
Fig. 3. UE-terminated session signaling message flow.
Fig. 4. Intra-MME/SGW HO signaling flows.
interface between source and destination eNodeB exists∗
.
The intra-MME/inter-SGW HO signaling flows contain two
additional pairs of signaling messages. The first pair between
MME and source S-GW (SSGW) release the bearer, while
the second pairs between MME and target S-GW (TSGW)
establish the bearer.
The inter-MME HO happens when more than one MME
is available in the network. Upon HO the UE can stay with
a given S-GW (i.e., inter-MME/intra-SGW HO) or changes
its S-GW (i.e., inter-MME/SGW HO). The source MME (S-
MME) controls the source eNodeB (SeNB) and source S-
GW (S-SGW) [if applicable], while the target MME (T-MME)
controls target eNodeB (T-eNB) and target S-GW (T-SGW) [if
applicable]. The message flow and description of the procedure
for inter-MME HO is depicted in Fig. 5. These scenarios
assume that the HO initiation needs to use the S2 interface.
Tracking Area Update (TAU) happens when a UE detects
that it has entered a new tracking area. If so, the UE updates
the network with this new tracking area information. If this
new tracking area is served by same MME, then this MME
accepts the TAU and register a new location for this UE
without interaction with HSS. However, if the serving MME
changes (i.e., inter-MME TAU), then the network forwards the
TAU to target MME. Next, the target MME updates the HSS
database with this new location information and the identity of
the target MME. The HSS cancels the UE’s location in source
MME and send the UE’s subscription data to the target MME.
The Inter-MME TAU message flow is depicted in Fig. 6.
B. 5G
The 5th generation (5G) is the next generation of wireless
technology and is expected to be deployed in the post 2020
timeframe. Currently, there is a global discussion on the
∗If this interface does not exist, then the HO procedure is very similar to
the inter-MME HO except for the involvement of an MME coordinating the
HO signaling loads.
4. Fig. 5. Inter-MME/SGW HO signaling flows.
Fig. 6. TAU signaling flows.
definition of 5G [7]–[9]. NO recognized standards body has
yet defined 5G. There are several proposals for 5G network
architectures in literature [3], [14], [15]. These proposals
generally assume a network upgrade from an All-IP network
architecture, and utilize cloud technology and variety of
different radio access technologies.
There are many factors that are driving the development
of 5G such as: multi-gigabit per second (Multi-Gbps), Internet
of Things (IOT), ubiquitous access to mobile services, cloud
technology, software defined networks (SDNs), and increasing
service complexity (e.g., 3D video and gaming, augmented
reality, and self-driving cars). Study shows that telecommu-
nication services are increasingly to be virtualized and will
migrate to the cloud [10], [11]. While previous generations
of mobile networks were communication centric, 5G is about
both communication and computing. As a result 5G is expected
to extend the continuing revolution of moving the cloud to the
network in the form of a network embedded cloud.
To achieve higher data capacity, cell deployment will be
denser, i.e., gradually increasing up to ten times the density
of deployment in today’s networks [2]. Additionally, coop-
erative communication and joint processing techniques, such
as coordinated multi-point (CoMP), massive multiple-input-
multiple-output (MIMO), and joint radio resource scheduling
can be utilized to provide higher data rates. These methods
introduce additional cost due to interfering links and intensive
data exchange and computation. Additionally, the 5G core
network must be able to handle all of the control and user plane
traffic generated by the increasing large number of network
connected devices.
Based upon the different demands for communication
in the future it is unlikely that one network deployment
model be able to serve all use cases and scenarios in 2020.
As a result, flexibility to adapt to different scenarios with
different requirements will be an inherent part of future 5G
networks. One way to provide flexibility for future mobile
network deployment is leveraging cloud technology, specifi-
cally telecommunication cloud or network embedded cloud as
a distributed cloud architecture in which network providers add
data centers within their network to offer cloud services [12].
The distribution of cloud deployment in operator networks can
range from medium size data centers at a back office to Nano
data centers coexisting with a Base Station (BS). Operators
can exploit this cloud to offload the computing requirement of
mobile networks (e.g., cloud-radio access network (C-RAN)
or to virtualize mobile core network functions) [13].
III. INTERNET OF THINGS (IOT)
In a future networked society, every thing that benefits from
a connection will be connected. As a result, IOT communi-
cation such as MTC, vehicle-to-vehicle (V2V), Machine-to-
Machine (M2M), smart objects and sensors can be embedded
in almost everything everywhere. IOT can be described as
an application that communicates with other IOT devices
or servers within the cloud (either cloud inside or outside
an operator’s network) using a communication network and
without human interaction. IOT devices can use any type
of network for their communication, such as wireless local
area networks, mobile networks including UMTS, LTE, and
future 5G depending on the required QoS, cost, and network
support. As mobile networks already have significant coverage
in order to services to humans, they might also be used to
carry IOT traffics [16]. However, current mobile networks were
not designed for MTC, hence 5G aims to support the IOT by
meeting the requirements for this communication.
Monitoring information from embedded sensors, remote
device configuration, and triggering alarms based on data
received from IOT devices are examples of IOT applications.
IOT devices can have a fixed location (e.g., sensors measuring
humidity in environment or other sensors inside a smart home)
or be mobile (e.g., sensors embedded within a car, a human
body, or other moving objects).
Data generated by IOT devices differs from data generates
by humans. Additionally, not all MTC applications have the
5. same characteristics [17]. IOT data can be small in size but
frequently transmitted. IOT may deploy billions of devices
(i.e., many more than the number of humans). The increasing
numbers of devices utilizing a mobile network is a primary
concern and may lead to problems such as congestion and
overhead both on the data and control planes. Congestion can
occur both in the radio access and core network. Although
each IOT device may send and receive a small amount of
data, the cumulative traffic from all of these devices can lead
to congestion. Additionally, IOT devices also generate control
and signaling traffic (even while they only transfer a small
amount of data) due to their need to attach or re-attach to
the network, and this control traffic can negatively effect core
network control entities.
There is an ongoing discussion regarding the prerequisite
for the network to meet MTC demands [17], [18]. Additionally,
There efforts have been made to address congestion control
for IOT and MTC, especially for LTE network. J. Wang,
et al. [19] proposed TCP-FT as an enhancement for TCP
to reduce congestion. Another suggestion was group based
traffic management [20], where in each group only one IOT
device communicated directly to the mobile network, hence
reducing the control signaling overhead in mobile network.
The time controlled policy introduced by 3GPP [21] is another
suggestion, in which a device only can communicate with a
network if it is not in a blocked period. The intention of most of
these proposals is to reduce congestion caused by IOT devices
in the radio access network. This paper proposes a solution
to reduce the load and probability of congestion in the core
network control entities for 5G.
IV. PROPOSED SOLUTION
This proposal assumes that the 5G architecture will not be
limited by current flat LTE architecture. Fig. 7 describes the
proposed architecture for future 5G. In this proposal, The core
network consists of two categories of nodes: control nodes and
gateway nodes. Control nodes are responsible for processing
and handling control signaling, while gateway nodes are
responsible for handling user plane traffic. The proposed 5G
control node characteristics are
Fig. 7. Proposed 5G core architecture.
1) A control node is virtualized and realize all required
control functions, such as (re)attachment handling,
mobility management, authorization, and authentica-
tion.
2) Control node functions are independent and can
run independently, in the same or separate physical
locations.
3) Each of control function can be executed in a different
physical location while maintaining a parent-child
relationship.
4) Each control functions can act as a parent, a child, or
both. The child acts the same as its parent and is able
to update its parent if required. As a result, logically
from UE’s point of view, the parent and child looks
like a single entity.
5) Control functions communicate with each other when
needed.
One suggestion to manage control signaling traffic in order
to avoid congestion in the 5G core network is placing those
control functions that make high demands upon the network
due to users, as a child function close to UE’s current radio
access point. Combining the telecommunication cloud and
the proposed 5G control node characteristics are the primary
enablers for this proposal. In this way, control functions can
be launched as a child in data centers within the core network
or data centers co-located with radio base stations. An SDN
can be employed to provide a communication between parent
and child control functions, i.e., enabling the child to migrate
to an other location.
To achieve this goal, the design and implementation of
the control node should be done such that it can satisfies the
proposed characteristic of the 5G core network. The benefit
of this approach is that by distributing control functions as
a children running close to UEs, the signaling load can
be processed and handled locally. Additionally, this reduces
the response time to control function requests. Moreover,
the parent control functions are unaffected by a amount of
signaling traffic that might be generated by large numbers
of UE, such as IOT devices. Finally, this approach reduces
the control plane’s bandwidth consumption, while adding
additional capacity to the core network to handle user plane
traffic.
Fig. 8 a flow chart describing how this solution works.
Assumes that fp
m is a control function M running at a control
node as a parent. Also assume that DC1 exists in or near
the BS that serves UE1. When “function M” is needed by
UE1, and if function Ms child (fc
m) exists close to BS for
UE1, then fc
m serves the UE’s request and updates fp
m [if
required]. If fc
m does not exist, then the request is routed
to fp
m at the main control node. Now fp
m serves the request
and launches fc
m close to BS (i.e., inside DC1). The primary
control node decides whether fm should execute as a child
(i.e., close to UE1) or not. This assume that there will
be collaboration between network management and cloud
management. There are ongoing activities such as EU FP7
Project UNIFY that addresses collaboration between the cloud
and network management [22].
V. SIGNALING LOAD ANALYSIS
This section gives a mathematical model that can be used
to calculate the control node(s) signaling load for a future
6. Fig. 8. De-centralized control plane function procedure.
mobile communication platform. For this purpose, we assume
that there are four control plane events that initiate signaling
control in LTE (as described earlier in SectionII-A) remains in
future 5G. Another simplifying assumption is that each IOT
device supports one application.
Let λo denotes the average number of originated session
by an IOT application per second and λt denotes the average
number of session terminating at an IOT device per second.
If λo and λt are independent events, the probability of IOT
device being active in a terminated session (PAT ) when the
IOT device wishes to send data is:
PAT = λt × γt (1)
Where γt is the average duration of originated session (in
seconds). Further, let “ρ” represents the density of IOT devices
per km2
, “A” represents coverage area by each cell (in km2
),
and “C” denotes the total number of cells in an operator
network’s. Additionally, introduce “K” a distribution factor for
each control function. If K = 1, then a central control function
in the network manages all related control events within a
network, while K = C denotes a fully distributed approach
where control functions coexist with each BS. The number
of message processed by a control function (i.e., messages
entering or leaving the control function) due to IOT originated
sessions is given by
Lo =
Mo × λo × ρ × A × C × (1 − PAT )
K
(2)
where Mo denotes number of control messages processed by
control function(s). It worth considering that when a UE is
in CONNECT mode in a UE-terminated session, there is no
signaling overhead to set up a connection for originating a
session to send data. Also, if a UE is in CONNECT mode in
a UE originated session, there is no signaling overhead to set
up a connection for receiving data. As a result, for a UE in
idle state number of messages processed by the control node
(entering or leaving) due to UE-terminated session is given by
Lt =
Mt × λt × ρ × A × C × (1 − PAO)
K
(3)
where Mt denotes the number of control messages processed
by control function(s) to set up a connection for UE-terminated
session and PAO denotes the probability that an IOT device
is connected in a UE-originated session when data arrives for
an IOT device. From Fig.3 Mt = Mo + Ca + 1 for a LTE
network where Ca represents the number of eNodeBs per
tracking area∗
. Also, based on the independent assumption of
λo and λt, PAO can be calculated as
PAO = λo × γo (4)
where γout is the average duration of originated session
(in seconds). The load due to session management can be
calculated as
Lsm = Lo + Lt (5)
To calculate control node load due to hand over classical
Fluid-Flow Mobility [23] is employed to estimate a UE
HO rate. Based on this model for a circular region with a
population density of ρ, an average velocity ¯v, and region
diameter of D, the average number of site crossings per unit
time is Navg = ρπD¯v. The centralized approach of HO
management function (i.e., K = 1) presents a scenario where
a central HO function in the network manages all HOs within
a network and no changing of HO management node occurs
during HO. In this case, the total number of message per hour
at the control function due to HO is given by:
Lh
K=1 = [Mcsg
ncc × Pcsg + Mncsg
ncc × (1 − Pcsg)] × NavgPA × C
(6)
where Pcsg is S-GW relocation probability, Mcsg
ncc denotes the
number of HO signaling messages processed by the control
function when there is no change in control node and no
change in S-GW, Mncsg
ncc denotes number of HO signaling
messages processed by the control function when there is
no change in control node but S-GW relocation is required,
and PA denotes probability of device being in CONNECTED
mode. PA can be well approximated by PAT + PAO.
When K = C we have full distribution of HO management
entity. Also, we assume that co-located with each BS is an
embedded data center to host a control function for HO
management. We also assume that the rate of UEs leaving
a BS equals to the rate of UEs joining a BS as a result of
uniform user density. In this procedure there is possibility that
∗We assumes the paging message will not be lost on the back-haul or air
interface and there is no need for paging re-transmission.
7. a UE stays with same S-GW or S-GW relocation also occurs
during the HO procedure. As a result, the load on the HO
control function is sum of load on HO management function
as a source control function (Lsc) (i.e., due to UEs leave the
cell) and the loads on HO management function as a target
control function (Ltc) (i.e., due to UEs joining a cell). These
are given by
Lh
K=C = [(Mcsg
Lsc
+ Mcsg
Ltc
) × Pcsg + (Mncsg
Lsc
+ Mncsg
Lsc
) × (1 − Pcsg)] × Navg × PA
(7)
where Mcsg
Lsc
denotes the number of HO signaling messages
of the source HO function when S-GW relocation is required
and Mncsg
Lsc
denotes the number of HO signaling messages of
the source HO control function when the UE maintains the
same S-GW. Additionally, Mcsg
Ltc
denotes the number of HO
signaling messages on the target HO control function when
S-GW relocation is required and Mcsg
Ltc
denotes the number
of HO signaling messages on the target HO control function
when the UE maintains the same S-GW.
When 1 < k < C the coverage region divides to K areas∗
where each area has its own HO management entity. In this
case, the signaling load on the HO management entity in each
area is the sum of the load due to HO inside that area (i.e., HO
without changing HO management function) and the load due
to HO between two areas (i.e., HO cases when the UE changes
HO management function). The signaling load on each HO
management function can be approximated as
Lh
1<K<C = Lh
K=1 × ( 1
K − C
K ) + Lh
K=C × C
K
(8)
Another event that produces signaling load is TAU. If
K represents the distribution factor of tracking area, then
Ca = C
K . In this case, the total number of signaling messages
generated on the network due to tracking area update is
approximated as
LT AU = [(Mcsm
T AU ×Pcsm+(Mcsm
T AU ×(1−Pcsm)]×Navg×
√
C ∗ K
(9)
where Mcsm
T AU denotes the number of signaling messages for
intra-session management TAU, Mcsm
T AU denotes the number
of messages for inter-session management TAU, and Pcsm
represents the probability of changing session management
function when changing tracking area region. Pcsm can be
approximated as K
K when K ≤ K and to 1 for other cases.
VI. NUMERICAL ANALYSIS
This section presents the numerical analysis of the control
signaling load for both centralized and de-centralized control
approach. The assumption in future 5G is that the number
of signaling message processed at control functions for each
controlling event is equal to messages proceed at an LTE MME
due to same events (as discussed in section II-A). In this
analysis we assumed a region size of 1000 Km2
, and λo =
∗We assumes coverage region divides to equal pieces.
3λt = 1 per minute. Additionally, based on 5G UE terminal
target capacity (i.e., 10 Gbps) and the assumption of only a
very small amount of data being transmitted by IOT device
(i.e., assumed 500 Kb for up-link and 1500 Kb per down-link)
session duration can be calculated as γt = 3×γo = 1.5e−06.
finally, we assumed the average speed of devices ¯v = 20 km/h.
Equations 2 and equation 3 shows that user density and
the number of BSs connected to one session management
function are two factors that effect session management load
due to UE originated and UE terminated scenarios. As a
result, in future 5G deployments with denser cell deployment
and high user density, the load on the session management
function is expected to increase. One approach for reducing
this load would be to decrease the area covered by a session
management function (i.e., to reduce the number of BSs
attached to a single session management function). This
reduction can be a factor of co-locating session management
functions at each BS, i.e., session management distribution
factor K = C (as we discussed in section IV). Fig. 9 shows
how user density and the distribution factor of the session
management function effect the session management load. In
this figure we assumed that the size of a tracking area was
Ca = 10.
Table I gives examples of the number of messages pro-
cessed at each session management function due to UE
originated and UE terminated scenario in units of millions
of messages per hour. It is worth mentioning that increasing
distribution factor of session management function will not
effect the total number of signaling message in the network.
The total number of signaling message generated in the
network for different values of ρ is shown in the first column
of Table I when the K = 1.
TABLE I. NUMBER OF MESSAGES PROCEED AT THE SESSION
MANAGEMENT FUNCTION BASED ON SAMPLE VALUE OF K AND ρ IN
UNITS OF MILLIONS OF MESSAGES PER HOUR.
Distribution factor K =
1 100 200 300
ρ =
1000 556 5.56 2.78 1.853
4000 2224 22.24 11.12 7.413
8000 4448 44.48 22.24 14.827
‘Inter HO management function” describes a scenario
Fig. 9. Session management function load per hours based on session
management distribution factor K and user density ρ. The ”Z” axis uses
logarithm scale.
8. Fig. 10. HO management load based on HO management distribution factor
K and user densityρ. The ”Z” axis uses a logarithm scale.
wherein after HO the UE changes HO management function,
while ‘intra HO management function” is an HO within a
single HO management function coverage area. As discussed
previously, inter HO management function scenarios produce
greater load than intra HO management function scenarios. On
the other hand, increasing UE density or dense deployment of
BSs will increase HO rate in the mobile network resulting
in higher load. In a fully distributed HO management function
approach, all HOs are inter HO management function, but each
HO management function handles fewer HO. Fig. 10 shows
how increasing user density and the distribution factor of the
HO function affects the HO management function loads.
Table II gives an example of the number of messages
processed at each HO management function and the total HO
signaling load generated on the network when the user density
ρ = 8000 UE/Km2
. From this table, we can observe that
increasing the distribution factor of HO management function
will reduce the load on each HO management function but,
at the cost of increasing the total signaling load generated
on the network. However, the total number of messages per
hour is negligible. The high capacity of future 5G networks
and low amount of data transmitted in each communication
results in low value of PA (i.e., 8.340e − 09 based on our
assumptions). The low value for PA indicates a low probability
of a device being in a connected state when HO occurs, hence
the signaling between UE and HO management function are
unneeded.
TABLE II. NUMBER OF MESSAGES PER HOUR PROCESSED AT EACH
HO MANAGEMENT FUNCTION AND THE TOTAL LOAD GENERATED AT
NETWORK DUE TO HO WHEN THE ρ = 8000 AND BASED ON SAMPLE
VALUES OF K IN UNITS OF MESSAGES PER HOUR.
Distribution factor K =
1 100 200 300
Load at each
HO management
function
1.318 0.031 0.019 0.015
Total load gener-
ated due to HO
in network
1.318 3.093 3.910 4.538
The tracking area information will be utilized by session
management entities when there is incoming data for an idle
UE. Tracking area size affects the load generated because of
the need to send TAU (i.e., when a UE finds itself in new
Fig. 11. Number of signaling message proceed at each session management
function due to TAU based on different distribution factor for session
management K and and tracking area K . The ”Z” axis are in logarithm
scale.
Fig. 12. Number of signaling message proceed at each session management
function due to TAU based on different distribution factor for tracking area
K when session management K = 150.
tracking area it must send a TAU) and also the signaling load
due to the UE terminated scenario. In this part of the analysis,
we assume that the agent for handling TAU is co-located with
the session management functions. From equation 9, it is clear
that increasing user density results in linear growth of load
due to TAU. There are two more factors that can effect on
TAU: distribution factor of session management functions (K)
and the distribution factor of the tracking area (K ). These
two factors determine the number of BSs in one tracking area
and the number of tracking areas supported by one session
management. Fig. 11 shows how these two factors affect the
number of messages processed because of TAU.
Table III gives an example of the number of messages
processed at each session management function due to TAU
9. in units of millions messages per hour. It is worth mentioning
that increasing K result in more tracking area but with smaller
size thus increasing TAU load as the user more frequent needs
to send a TAU. K < K means that one TA will be covered
by numbers of session management. As a result, the load of
TAU will split between those session management functions
that result in slow growth in TA management function when
K increase. K > K means that each session management
function cover several TAs. As a result, the load on each
session management function will be the sum of the load
generated by each TA, thus leading to a rapid growth in
session management load when K increase. Fig. 12 depicts
this behavior when the session management distribution factor
K = 150.
TABLE III. NUMBER OF MESSAGES PROCEED AT SESSION
MANAGEMENT FUNCTION DUE TO TAU BASED ON SAMPLE VALUE OF
SESSION MANAGEMENT DISTRIBUTION FACTOR K AND TA DISTRIBUTION
FACTOR K IN UNITS OF MILLIONS MESSAGES PER HOUR.
K =
1 100 200 300
K =
1 53.808 0.538 0.269 0.179
100 1506.622 5.381 2.690 1.794
200 2175.261 12.067 3.805 2.537
300 2688.325 17.198 6.370 3.107
On the other hand, increasing the distribution factor of TAU
(i.e., results in smaller Ca) decreases the load on each session
management functions due to UE terminated sessions. As a
result from a session management function point of view the
maximum value possible for the TA distribution factor results
in lower load due to UE terminated scenarios. Based on the
assumption of co-locating the session management function
and TA management function to find appropriate value for
TA distribution factor the aggregation of UE termination and
TAU signaling load should be considered. Table IV shows
the number of messages processed at the session management
function due to UE originated and UE terminated scenario
based on sample values of K and K .
TABLE IV. AGGREGATION OF MESSAGES PROCEED AT SESSION
MANAGEMENT FUNCTION DUE TO TAU AND UE ORIGINATED AND UE
TERMINATED BASED ON SAMPLE VALUE OF SESSION MANAGEMENT
DISTRIBUTION FACTOR K AND TA DISTRIBUTION FACTOR K IN UNITS OF
MILLION MESSAGES PER HOUR.
K =
1 100 200 300
K =
1 5 61.474 0.615 0.308 0.205
100 1507.985 5.394 2.698 1.799
200 2176.592 12.081 3.811 2.541
300 2689.647 17.211 6.377 3.111
Fig. 13 shows how changing K and K effects on the total
number of message processed on the network due to handling
TAU. It worth mentioning that increasing the distribution factor
of TAU increase the total load generated due to TAU on
network. The pattern of increase is the same as shown Fig.
12. On the other hand, increasing the session management
distribution factor decreases the total TAU load on the network.
When K = K , the total load generated on the network due to
TAU will remain constant. Table V gives examples of the total
number of messages generated on the network due to TAU.
A. Discussion
Two factors are relevant when we are debating the dis-
tribution factor value for each control function, i.e., the
TABLE V. TOTAL NUMBER OF SIGNALING MESSAGE GENERATED
WITHIN NETWORK BASED ON SAMPLE VALUE OF SESSION MANAGEMENT
DISTRIBUTION FACTOR K AND TA DISTRIBUTION FACTOR K IN UNIT OF
MEGA MESSAGE PER HOUR.
K =
1 100 200 300
K =
1 53.801 53.808 53.808 53.808
100 1506.622 538.080 538.080 538.080
200 2175.261 1206.718 760.959 760.959
300 2688.325 1719.783 1274.024 931.980
signaling load on each function and total load generated within
the network for each control events. Reducing the load at
each control function by distributing those functions enables
network operators to better scale their network in order to
manage the huge number of signaling messages generated by
different types of users in a future 5G network. The second
factor that we should consider is the total number of messaged
generated on the network. A more highly loaded network
indicates a need for more compute resources and capacity both
of which will increase operational costs.
Increasing the “session management function” distribution
factor results in a division of session management signaling
messages to more session management functions without
adjusting the total number of session management signaling
messages in the network. As a result, increasing this factor
when user density increases is a reasonable action.
The high capacity of future 5G networks and limited data
transmitted by IOT devices affects most of the HO scenarios as
the UE is likely to stay in idle mode. In this case, a low amount
of HO signaling is expected (i.e., even in a network with very
high UE density) as for the idle UEs no signaling messages are
required between the UE and the HO management function.
As a result, the distribution of HO management function does
not add considerable value for the network operators. future
IOT device that are not concerned with battery consumption
can choose ‘always-on” ∗
approach that raise signaling load
because of HO. On the other hand, for devices with ”always-
on” approach session management function signaling load
will decrease as there is no paging and session management
required. Further study is needed to analyze the side effect of
the always-on approach, but this is out of the scope of this
paper.
The TA distribution factor determines the size and number
of TAs covered by each session management. A larger value
for the TA distribution factor will result in lower load for UE
terminated scenarios, while increasing the aggregated load due
to the TAU on the network.
VII. CONCLUSION
This paper discusses a novel control plane architecture for
future 5G to provide a flexible and scalable network. The
proposed network architecture consists of independent control
function responsible for different control events in the network.
The control functions can leverage cloud technologies (e.g.,
network embedded cloud) and run in a virtualized environment
to implement a flexible and scalable control plane function
distributed within 5G mobile networks. This approach aims to
enable 5G networks to manage the enormous amount of control
∗This approach keeps continuously UEs in a connected state.
10. Fig. 13. Total number of signaling message proceed at network due to TAU based on different distribution factor for tracking area K and distribution factor
fo session management K.
signaling produce by IOT and MTC. We utilized 3GPP LTE
to identify the required control plane events, and we assumed
that 5G takes evolutionary path from LTE. We have shown that
moving the control plane session management function close
to UEs at a data center co-located with the BS is beneficial in
terms of control signaling load management.
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