A multi-layered satellite network consisting of geosynchronous and nano-satellites is suited to perform
space situational awareness. The nano-satellites collect information of space objects and transfer data to
ground stations through the geosynchronous satellites. The dynamic topology of the network, large
propagation delays and bulk data transfers results in a congested network. In this paper, we present a
convex optimization based congestion control algorithm. Using snapshots of the network, operating
parameters such as incoming, outgoing rates and buffer utilization are monitored. The operating
parameters of a satellite are formulated as a convex function and using convex optimization techniques, the
incoming data rates are evaluated to minimize congestion. Performance comparison of our algorithm with
Transmission Control Protocol congestion control mechanism is presented. The simulation results show
that our algorithm reduces congestion while facilitating higher transmission rates.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
Effective Router Assisted Congestion Control for SDN IJECEIAES
Router Assisted Congestion Control (RACC) was designed to improve endto-end congestion control performance by using prior knowledge on network condition. However, the traditional Internet does not provide such information, which makes this approach is not feasible to deliver. Our paper addresses this network information deficiency issue by proposing a new congestion control method that works on the Software Defined Network (SDN) framework. We call this proposed method as PACEC (Path Associativity Centralized Congestion Control). In SDN, global view of the network information contains the network topology including link properties (i.e., type, capacity, power consumption, etc.). PACEC uses this information to determine the feedback signal, in order for the source to start sending data at a high rate and to quickly reach fair-share rate. The simulation shows that the efficiency and fairness of PACEC are better than Transmission Control Protocol (TCP) and Rate Control Protocol (RCP).
TOPOLOGY DISCOVERY IN MULTI-HOP CLUSTERING VEHICULAR NETWORKScaijjournal
In this paper, we propose a novel multi-hop cluster architecture for location service protocol in vehicular ad
hoc networks. The proposed scheme uses two parameters which are the connectivity between vehicles and the
vehicle mobility to select cluster head. The performance of the proposed scheme is the tradeoff between the
vehicle locations and the communication overheads. The proposed scheme is not only scalable but also
reliable and is able to achieve high load balancing with fast convergence. The cluster constructed by the
proposed scheme is more stable than exiting vehicular ad hoc network clustering schemes. Specifically, the
proposed scheme can increase the cluster-head lifetime up to 50%. The reason behind this achievement is
that the proposed scheme considers vehicle mobility in terms of average link expiration time while selecting
cluster-head.
QoS based Admission Control using Multipath Scheduler for IP over Satellite N...IJECEIAES
This paper presents a novel scheduling algorithm to support quality of service (QoS) for multiservice applications over integrated satellite and terrestrial networks using admission control system with multipath selection capabilities. The algorithm exploits the multipath routing paradigm over LEO and GEO satellites constellation in order to achieve optimum end-toend QoS of the client-server Internet architecture for HTTP web service, file transfer, video streaming and VoIP applications. The proposed multipath scheduler over the satellite networks advocates load balancing technique based on optimum time-bandwidth in order to accommodate the burst of application traffics. The method tries to balance the bandwidth load and queue length on each link over satellite in order to fulfil the optimum QoS level for each traffic type. Each connection of a traffic type will be routed over a link with the least bandwidth load and queue length at current time in order to avoid congestion state. The multipath routing scheduling decision is based on per connection granularity so that packet reordering at the receiver side could be avoided. The performance evaluation of IP over satellites has been carried out using multiple connections, different file sizes and bit-errorrate (BER) variations to measure the packet delay, loss ratio and throughput.
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Resource Allocation Optimization for Heterogeneous NetworkIOSRjournaljce
The improvement of communication throughput using a cross layer mode of communication is proposed. Due to critical mode of applications of sensor networks, it is required to achieve data at faster rate for high refreshment. As the communicating data’s are sensed or measured data, it is required to have higherthroughput and less interference, to achieve accuracy and optimal resource utilization. In this paper we propose aintegrated cross layer mechanism to achieve higher performance in sensor networks. A new approach of cross layer controlling, based on integrated factor of power allocationand memory blockage is proposed.This mode of communication results at faster data transfer, with lower energy resource consumption over a wirelesssensor network architecture.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
Effective Router Assisted Congestion Control for SDN IJECEIAES
Router Assisted Congestion Control (RACC) was designed to improve endto-end congestion control performance by using prior knowledge on network condition. However, the traditional Internet does not provide such information, which makes this approach is not feasible to deliver. Our paper addresses this network information deficiency issue by proposing a new congestion control method that works on the Software Defined Network (SDN) framework. We call this proposed method as PACEC (Path Associativity Centralized Congestion Control). In SDN, global view of the network information contains the network topology including link properties (i.e., type, capacity, power consumption, etc.). PACEC uses this information to determine the feedback signal, in order for the source to start sending data at a high rate and to quickly reach fair-share rate. The simulation shows that the efficiency and fairness of PACEC are better than Transmission Control Protocol (TCP) and Rate Control Protocol (RCP).
TOPOLOGY DISCOVERY IN MULTI-HOP CLUSTERING VEHICULAR NETWORKScaijjournal
In this paper, we propose a novel multi-hop cluster architecture for location service protocol in vehicular ad
hoc networks. The proposed scheme uses two parameters which are the connectivity between vehicles and the
vehicle mobility to select cluster head. The performance of the proposed scheme is the tradeoff between the
vehicle locations and the communication overheads. The proposed scheme is not only scalable but also
reliable and is able to achieve high load balancing with fast convergence. The cluster constructed by the
proposed scheme is more stable than exiting vehicular ad hoc network clustering schemes. Specifically, the
proposed scheme can increase the cluster-head lifetime up to 50%. The reason behind this achievement is
that the proposed scheme considers vehicle mobility in terms of average link expiration time while selecting
cluster-head.
QoS based Admission Control using Multipath Scheduler for IP over Satellite N...IJECEIAES
This paper presents a novel scheduling algorithm to support quality of service (QoS) for multiservice applications over integrated satellite and terrestrial networks using admission control system with multipath selection capabilities. The algorithm exploits the multipath routing paradigm over LEO and GEO satellites constellation in order to achieve optimum end-toend QoS of the client-server Internet architecture for HTTP web service, file transfer, video streaming and VoIP applications. The proposed multipath scheduler over the satellite networks advocates load balancing technique based on optimum time-bandwidth in order to accommodate the burst of application traffics. The method tries to balance the bandwidth load and queue length on each link over satellite in order to fulfil the optimum QoS level for each traffic type. Each connection of a traffic type will be routed over a link with the least bandwidth load and queue length at current time in order to avoid congestion state. The multipath routing scheduling decision is based on per connection granularity so that packet reordering at the receiver side could be avoided. The performance evaluation of IP over satellites has been carried out using multiple connections, different file sizes and bit-errorrate (BER) variations to measure the packet delay, loss ratio and throughput.
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Resource Allocation Optimization for Heterogeneous NetworkIOSRjournaljce
The improvement of communication throughput using a cross layer mode of communication is proposed. Due to critical mode of applications of sensor networks, it is required to achieve data at faster rate for high refreshment. As the communicating data’s are sensed or measured data, it is required to have higherthroughput and less interference, to achieve accuracy and optimal resource utilization. In this paper we propose aintegrated cross layer mechanism to achieve higher performance in sensor networks. A new approach of cross layer controlling, based on integrated factor of power allocationand memory blockage is proposed.This mode of communication results at faster data transfer, with lower energy resource consumption over a wirelesssensor network architecture.
Energy balanced improved leach routing protocol for wireless sensor networkscsandit
A proper sensor node clustering is an effective topology control that can balance energy
consumption among sensor nodes and increase network scalability and life time. As the use of
wireless sensor networks (WSNs) has grown enormously, the need for energy-efficient routing
and data aggregation has also risen. LEACH
(
Low Energy Adaptive Cluster Hierarchy
)
is a
hierarchical clustering protocol that provides an elegant solution for such protocols. Random
clustering is the main deficiency of LEACH. In this paper an energy balanced clustering
approach is proposed, in which the K-mean clustering algorithm is applied. It is centralized
clustering algorithm that based on minimum energy clustering to form optimal clusters. For the
candidate nodes, the location and the residual energy are used as key parameters to select the
cluster head (CH). The method shows that the proposed approach outperforms LEACH in terms
of energy conservation and network life time prolonging.
Congestion Control in Wireless Sensor Networks Using Genetic AlgorithmEditor IJCATR
Sensor network consists of a large number of small nods, strongly interacting with the physical environment, takes
environmental data through sensors, and reacts after processing on information. Wireless network technologies are widely used in most
applications. As wireless sensor networks have many activities in the field of information transmission, network congestion cannot be
thus avoided. So it seems necessary that some new methods can control congestion and use existing resources for providing better traffic
demands. Congestion increases packet loss and retransmission of removed packets and also wastes of energy. In this paper, a novel
method is presented for congestion control in wireless sensor networks using genetic algorithm. The results of simulation show that the
proposed method, in comparison with the algorithm LEACH, can significantly improve congestion control at high speeds.
Prediction of traveller information and route choiceayishairshad
ayisha irshad ppt Subjected presentation is based on a research paper by
Afzal Ahmeda, Dong Ngoduya & David Watlinga
a Institute for Transport Studies, University of Leeds, 34–40
University Road, Leeds LS2 9JT, UK Published online: 10 Jun 2015.
Newton-raphson method to solve systems of non-linear equations in VANET perfo...journalBEEI
Nowadays, Vehicular Ad-Hoc Network (VANET) has got more attention from the researchers. The researchers have studied numerous topics of VANET, such as the routing protocols of VANET and the MAC protocols of VANET. The aim of their works is to improve the network performance of VANET, either in terms of energy consumption or packet delivery ratio (PDR) and delay. For this research paper, the main goal is to find the coefficient of a, b and c of three non-linear equations by using a Newton- Raphson method. Those three non-linear equations are derived from a different value of Medium Access Control (MAC) protocol's parameters. After that, those three coefficient is then will be used in optimization of the VANET in terms of energy, PDR, and delay.
Influence of Clustering on the Performance of MobileAd Hoc Networks (MANETs)Narendra Singh Yadav
Clustering is an important research area for mobile ad hoc networks (MANETs) as it increases the capacity of network, reduces the routing overhead and makes the network more scalable in the presence of both high mobility and a large number of mobile nodes. Routing protocols based on flat topology are not scalable because of their built-in characteristics. However, clustering cause overhead which consumes considerable bandwidth, drain mobile nodes energy quickly, likely cause congestion, collision and data delay in larger networks. This paper uses an implementation of the Dynamic Source Routing (DSR), an flat architecture based and the Cluster Based Routing Protocol (CBRP), a cluster architecture based routing protocol to examine the influence of clustering on the performance of mobile ad hoc networks. This paper evaluates channel utilization and control overhead as a function of number of nodes per sq. km to show the effect of clustering. Simulation results show that in high mobility scenarios, CBRP outperforms DSR. CBRP scales well with increasing number of nodes.
Incorporate ACO routing algorithm and mobile sink in wireless sensor networks IJECEIAES
Today, science and technology is developing, particularly the internet of things (IoT), there is an increasing demand in the sensor field to serve the requirements of individuals within modern life. Wireless sensor networks (WSNs) was created to assist us to modernize our lives, saving labor, avoid dangers, and that bring high efficiency at work. There are many various routing protocols accustomed to increase the ability efficiency and network lifetime. However, network systems with one settled sink frequently endure from a hot spots issue since hubs close sinks take a lot of vitality to forward information amid the transmission method. In this paper, the authors proposed combining the colony optimization algorithm ant colony optimization (ACO) routing algorithm and mobile sink to deal with that drawback and extend the network life. The simulation results on MATLAB show that the proposed protocol has far better performance than studies within the same field.
Mobile environment pretense a number of novel
theoretical and optimization issues such as position, operation
and following in that a lot of requests rely on them for
desirable information. The precedent works are sprinkled
across the entire network layer: from the medium of physical
to link layer to routing and then application layer. In this
invention, we present outline solutions in Medium Access
Control (MAC), data distribution, coverage resolve issues
under mobile ad-hoc network environment based on
congestion control technique using Transmission Control
Protocol (TCP). In mobile ad-hoc network issues can arise
such as link disconnections, channel contention and recurrent
path loss. To resolve this issue, we propose a Cross Layer
based Hybrid fuzzy ad-hoc rate based Congestion Control
(CLHCC) approach to maximize network performance. Based
on the destination report it regulates the speed of data flow to
control data loss by monitoring the present network status
and transmits this report to the source as advice. The source
adjusts the sending flow rate as per the advice. This is
monitored by channel usage, ultimate delay, short term
throughput.
GRAPH THEORETIC ROUTING ALGORITHM (GTRA) FOR MOBILE AD-HOC NETWORKS (MANET)graphhoc
Battlefield theater applications require supporting large number of nodes. It can facilitate many multi-hop
paths between each source and destination pairs. For scalability, it is critical that for supporting network
centric applications with large set of nodes require hierarchical approach to designing networks. In this
research we consider using Mobile Ad Hoc Network (MANET) with multiple clusters. Each cluster
supports a few nodes with a cluster head. The intra-cluster connectivity amongst the nodes within the
cluster is supported by multi-hop connectivity to ensure handling mobility in such a way that no service
disruption can occur. The inter-cluster connectivity is also achieved by multi-hop connectivity. However,
for inter-cluster communications, only cluster heads are connected. The selection of intra-cluster
communications and inter-cluster communications allow scalability of the network to support multiservices
applications end-to-end with a desired Quality of Service (QoS). This paper proposes graph
theoretic approach to establish efficient connection between a source and a destination within each cluster
in intra-cluster network and between clusters in inter-cluster network. Graph theoretic approach
traditionally was applied networks where nodes are static or fixed. In this paper, we have applied the
graph theoretic routing to MANET where nodes are mobile. One of the important challenges in MANET is
to support an efficient routing algorithm for multi-hop communications across many nodes which are
dynamic in nature. However, dynamic behavior of the nodes requires greater understanding of the node
degree and mobility at each instance of time in order to maintain end-to-end QoS for multi-service
provisioning. This paper demonstrates graph theoretic approach produces an optimum multi-hop
connectivity path based on cumulative minimum degree that minimizes the contention and scheduling
delay end-to-end. It is applied to both intra-cluster communications as well as inter-cluster
communications. The performance shows that having a multi-hop connectivity for intra-cluster
communications is more power efficient compared to broadcast of information with maximum power
coverage. Each cluster performs similarly and the algorithm is also used for inter-cluster communications.
Our simulation results show that the proposed graph theoretic routing approach will reduce the overall
delay and improves the physical layer data frame transmission.
An efficient reconfigurable geographic routing congestion control algorithm f...IJECEIAES
In recent times, huge data is transferred from source to destination through multi path in wireless sensor networks (WSNs). Due to this more congestion occurs in the communication path. Hence, original data will be lost and delay problems arise at receiver end. The above-mentioned drawbacks can be overcome by the proposed efficient reconfigurable geographic routing congestion control (RgRCC) algorithm for wireless sensor networks. the proposed algorithm efficiently finds the node’s congestion status with the help queue length’s threshold level along with its change rate. Apart from this, the proposed algorithm re-routes the communication path to avoid congestion and enhances the strength of scalability of data communication in WSNs. The proposed algorithm frequently updates the distance between the nodes and by-pass routing holes, common for geographical routing. when the nodes are at the edge of the hole, it will create congestion between the nodes in WSNs. Apart from this, more nodes sink due to congestion. it can be reduced with the help of the proposed RgRCC algorithm. As per the simulation analysis, the proposed work indicates improved performance in comparison to conventional algorithm. By effectively identifying the data congestion in WSNs with high scalability rate as compared to conventional methods
A fuzzy congestion controller to detect and balance congestion in wsnijwmn
A Wireless Sensor Network (WSN) is collection of wireless sensors with limited memory, processing and energy supply. Based on application, sensors distribute in a wide geographically area in order to collect information and transmit the collected data packets toward a base station also called Sink. Due to the relatively high node density and source-to-sink communication pattern, congestion is a critical issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy consumption as well as delay. To address this problem, in this paper we propose a new fuzzy logic based mechanism to detect and control congestion in each grid in WSN. In the proposed approach, sink select one node in each grid as Monitor Node. In addition, sink defines congestion candidate grids. Each Monitor Node in congestion candidate grids continually monitors the network and fetches the fuzzy controller inputs in order to determine level of congestion in each grid. Based on the congestion level, packets forward through the grid or relay nodes. Simulation results show that our approach has higher packet delivery ratio and lower packet loss than existing approaches.
A FUZZY-BASED CONGESTION CONTROLLER FOR CONTROL AND BALANCE CONGESTION IN GRI...cscpconf
A Wireless Sensor Network (WSN) is deployed with a large number of sensors with limited power supply in a wide geographically area. These sensors collect information depending on application. The sensors transmit the data towards a base station called sink. Due to the relatively high node density and source-to-sink communication pattern, congestion is a critical issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy
consumption as well as delay. To address this problem, in this paper we propose a new fuzzy logic based mechanism to detect and control congestion in WSN. In the proposed approach, a
Monitor Node for each grid in congestion candidate region performs a fuzzy control to avoid increasing congestion. Fuzzy controller’s inputs are continually fetched from the network by the Monitor Node. Simulation results show that our approach has higher packet delivery ratio and lower packet loss than existing approaches.
A fuzzy based congestion controller for control and balance congestion in gri...csandit
A Wireless Sensor Network (WSN) is deployed with a large number of sensors with limited
power supply in a wide geographically area. These sensors collect information depending on
application. The sensors transmit the data towards a base station called sink. Due to the
relatively high node density and source-to-sink communication pattern, congestion is a critical
issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy
consumption as well as delay. To address this problem, in this paper we propose a new fuzzy
logic based mechanism to detect and control congestion in WSN. In the proposed approach, a
Monitor Node for each grid in congestion candidate region performs a fuzzy control to avoid
increasing congestion. Fuzzy controller’s inputs are continually fetched from the network by the
Monitor Node. Simulation results show that our approach has higher packet delivery ratio and
lower packet loss than existing approaches.
Energy balanced improved leach routing protocol for wireless sensor networkscsandit
A proper sensor node clustering is an effective topology control that can balance energy
consumption among sensor nodes and increase network scalability and life time. As the use of
wireless sensor networks (WSNs) has grown enormously, the need for energy-efficient routing
and data aggregation has also risen. LEACH
(
Low Energy Adaptive Cluster Hierarchy
)
is a
hierarchical clustering protocol that provides an elegant solution for such protocols. Random
clustering is the main deficiency of LEACH. In this paper an energy balanced clustering
approach is proposed, in which the K-mean clustering algorithm is applied. It is centralized
clustering algorithm that based on minimum energy clustering to form optimal clusters. For the
candidate nodes, the location and the residual energy are used as key parameters to select the
cluster head (CH). The method shows that the proposed approach outperforms LEACH in terms
of energy conservation and network life time prolonging.
Congestion Control in Wireless Sensor Networks Using Genetic AlgorithmEditor IJCATR
Sensor network consists of a large number of small nods, strongly interacting with the physical environment, takes
environmental data through sensors, and reacts after processing on information. Wireless network technologies are widely used in most
applications. As wireless sensor networks have many activities in the field of information transmission, network congestion cannot be
thus avoided. So it seems necessary that some new methods can control congestion and use existing resources for providing better traffic
demands. Congestion increases packet loss and retransmission of removed packets and also wastes of energy. In this paper, a novel
method is presented for congestion control in wireless sensor networks using genetic algorithm. The results of simulation show that the
proposed method, in comparison with the algorithm LEACH, can significantly improve congestion control at high speeds.
Prediction of traveller information and route choiceayishairshad
ayisha irshad ppt Subjected presentation is based on a research paper by
Afzal Ahmeda, Dong Ngoduya & David Watlinga
a Institute for Transport Studies, University of Leeds, 34–40
University Road, Leeds LS2 9JT, UK Published online: 10 Jun 2015.
Newton-raphson method to solve systems of non-linear equations in VANET perfo...journalBEEI
Nowadays, Vehicular Ad-Hoc Network (VANET) has got more attention from the researchers. The researchers have studied numerous topics of VANET, such as the routing protocols of VANET and the MAC protocols of VANET. The aim of their works is to improve the network performance of VANET, either in terms of energy consumption or packet delivery ratio (PDR) and delay. For this research paper, the main goal is to find the coefficient of a, b and c of three non-linear equations by using a Newton- Raphson method. Those three non-linear equations are derived from a different value of Medium Access Control (MAC) protocol's parameters. After that, those three coefficient is then will be used in optimization of the VANET in terms of energy, PDR, and delay.
Influence of Clustering on the Performance of MobileAd Hoc Networks (MANETs)Narendra Singh Yadav
Clustering is an important research area for mobile ad hoc networks (MANETs) as it increases the capacity of network, reduces the routing overhead and makes the network more scalable in the presence of both high mobility and a large number of mobile nodes. Routing protocols based on flat topology are not scalable because of their built-in characteristics. However, clustering cause overhead which consumes considerable bandwidth, drain mobile nodes energy quickly, likely cause congestion, collision and data delay in larger networks. This paper uses an implementation of the Dynamic Source Routing (DSR), an flat architecture based and the Cluster Based Routing Protocol (CBRP), a cluster architecture based routing protocol to examine the influence of clustering on the performance of mobile ad hoc networks. This paper evaluates channel utilization and control overhead as a function of number of nodes per sq. km to show the effect of clustering. Simulation results show that in high mobility scenarios, CBRP outperforms DSR. CBRP scales well with increasing number of nodes.
Incorporate ACO routing algorithm and mobile sink in wireless sensor networks IJECEIAES
Today, science and technology is developing, particularly the internet of things (IoT), there is an increasing demand in the sensor field to serve the requirements of individuals within modern life. Wireless sensor networks (WSNs) was created to assist us to modernize our lives, saving labor, avoid dangers, and that bring high efficiency at work. There are many various routing protocols accustomed to increase the ability efficiency and network lifetime. However, network systems with one settled sink frequently endure from a hot spots issue since hubs close sinks take a lot of vitality to forward information amid the transmission method. In this paper, the authors proposed combining the colony optimization algorithm ant colony optimization (ACO) routing algorithm and mobile sink to deal with that drawback and extend the network life. The simulation results on MATLAB show that the proposed protocol has far better performance than studies within the same field.
Mobile environment pretense a number of novel
theoretical and optimization issues such as position, operation
and following in that a lot of requests rely on them for
desirable information. The precedent works are sprinkled
across the entire network layer: from the medium of physical
to link layer to routing and then application layer. In this
invention, we present outline solutions in Medium Access
Control (MAC), data distribution, coverage resolve issues
under mobile ad-hoc network environment based on
congestion control technique using Transmission Control
Protocol (TCP). In mobile ad-hoc network issues can arise
such as link disconnections, channel contention and recurrent
path loss. To resolve this issue, we propose a Cross Layer
based Hybrid fuzzy ad-hoc rate based Congestion Control
(CLHCC) approach to maximize network performance. Based
on the destination report it regulates the speed of data flow to
control data loss by monitoring the present network status
and transmits this report to the source as advice. The source
adjusts the sending flow rate as per the advice. This is
monitored by channel usage, ultimate delay, short term
throughput.
GRAPH THEORETIC ROUTING ALGORITHM (GTRA) FOR MOBILE AD-HOC NETWORKS (MANET)graphhoc
Battlefield theater applications require supporting large number of nodes. It can facilitate many multi-hop
paths between each source and destination pairs. For scalability, it is critical that for supporting network
centric applications with large set of nodes require hierarchical approach to designing networks. In this
research we consider using Mobile Ad Hoc Network (MANET) with multiple clusters. Each cluster
supports a few nodes with a cluster head. The intra-cluster connectivity amongst the nodes within the
cluster is supported by multi-hop connectivity to ensure handling mobility in such a way that no service
disruption can occur. The inter-cluster connectivity is also achieved by multi-hop connectivity. However,
for inter-cluster communications, only cluster heads are connected. The selection of intra-cluster
communications and inter-cluster communications allow scalability of the network to support multiservices
applications end-to-end with a desired Quality of Service (QoS). This paper proposes graph
theoretic approach to establish efficient connection between a source and a destination within each cluster
in intra-cluster network and between clusters in inter-cluster network. Graph theoretic approach
traditionally was applied networks where nodes are static or fixed. In this paper, we have applied the
graph theoretic routing to MANET where nodes are mobile. One of the important challenges in MANET is
to support an efficient routing algorithm for multi-hop communications across many nodes which are
dynamic in nature. However, dynamic behavior of the nodes requires greater understanding of the node
degree and mobility at each instance of time in order to maintain end-to-end QoS for multi-service
provisioning. This paper demonstrates graph theoretic approach produces an optimum multi-hop
connectivity path based on cumulative minimum degree that minimizes the contention and scheduling
delay end-to-end. It is applied to both intra-cluster communications as well as inter-cluster
communications. The performance shows that having a multi-hop connectivity for intra-cluster
communications is more power efficient compared to broadcast of information with maximum power
coverage. Each cluster performs similarly and the algorithm is also used for inter-cluster communications.
Our simulation results show that the proposed graph theoretic routing approach will reduce the overall
delay and improves the physical layer data frame transmission.
An efficient reconfigurable geographic routing congestion control algorithm f...IJECEIAES
In recent times, huge data is transferred from source to destination through multi path in wireless sensor networks (WSNs). Due to this more congestion occurs in the communication path. Hence, original data will be lost and delay problems arise at receiver end. The above-mentioned drawbacks can be overcome by the proposed efficient reconfigurable geographic routing congestion control (RgRCC) algorithm for wireless sensor networks. the proposed algorithm efficiently finds the node’s congestion status with the help queue length’s threshold level along with its change rate. Apart from this, the proposed algorithm re-routes the communication path to avoid congestion and enhances the strength of scalability of data communication in WSNs. The proposed algorithm frequently updates the distance between the nodes and by-pass routing holes, common for geographical routing. when the nodes are at the edge of the hole, it will create congestion between the nodes in WSNs. Apart from this, more nodes sink due to congestion. it can be reduced with the help of the proposed RgRCC algorithm. As per the simulation analysis, the proposed work indicates improved performance in comparison to conventional algorithm. By effectively identifying the data congestion in WSNs with high scalability rate as compared to conventional methods
A fuzzy congestion controller to detect and balance congestion in wsnijwmn
A Wireless Sensor Network (WSN) is collection of wireless sensors with limited memory, processing and energy supply. Based on application, sensors distribute in a wide geographically area in order to collect information and transmit the collected data packets toward a base station also called Sink. Due to the relatively high node density and source-to-sink communication pattern, congestion is a critical issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy consumption as well as delay. To address this problem, in this paper we propose a new fuzzy logic based mechanism to detect and control congestion in each grid in WSN. In the proposed approach, sink select one node in each grid as Monitor Node. In addition, sink defines congestion candidate grids. Each Monitor Node in congestion candidate grids continually monitors the network and fetches the fuzzy controller inputs in order to determine level of congestion in each grid. Based on the congestion level, packets forward through the grid or relay nodes. Simulation results show that our approach has higher packet delivery ratio and lower packet loss than existing approaches.
A FUZZY-BASED CONGESTION CONTROLLER FOR CONTROL AND BALANCE CONGESTION IN GRI...cscpconf
A Wireless Sensor Network (WSN) is deployed with a large number of sensors with limited power supply in a wide geographically area. These sensors collect information depending on application. The sensors transmit the data towards a base station called sink. Due to the relatively high node density and source-to-sink communication pattern, congestion is a critical issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy
consumption as well as delay. To address this problem, in this paper we propose a new fuzzy logic based mechanism to detect and control congestion in WSN. In the proposed approach, a
Monitor Node for each grid in congestion candidate region performs a fuzzy control to avoid increasing congestion. Fuzzy controller’s inputs are continually fetched from the network by the Monitor Node. Simulation results show that our approach has higher packet delivery ratio and lower packet loss than existing approaches.
A fuzzy based congestion controller for control and balance congestion in gri...csandit
A Wireless Sensor Network (WSN) is deployed with a large number of sensors with limited
power supply in a wide geographically area. These sensors collect information depending on
application. The sensors transmit the data towards a base station called sink. Due to the
relatively high node density and source-to-sink communication pattern, congestion is a critical
issue in WSN. Congestion not only causes packet loss, but also leads to excessive energy
consumption as well as delay. To address this problem, in this paper we propose a new fuzzy
logic based mechanism to detect and control congestion in WSN. In the proposed approach, a
Monitor Node for each grid in congestion candidate region performs a fuzzy control to avoid
increasing congestion. Fuzzy controller’s inputs are continually fetched from the network by the
Monitor Node. Simulation results show that our approach has higher packet delivery ratio and
lower packet loss than existing approaches.
Optimal resource allocation in networked control systems using viterbi algorithmjournalBEEI
This paper presents an optimal bandwidth allocation method for a networked control system (NCS) which includes time-driven sensor, event-driven controller and random channels. A hidden markov model (HMM) with a discretized state space is formulated for the random traffic to predict the network states using a suitable data window. Network bandwidth is allocated based on the predicted traffic state subject to bounds on the deterministic traffic that guarantee acceptable NCS performance and do not exceed hardware limitations. Bandwidth allocation uses minimization of unmet bandwidth demand. A stability condition is derived for a variable but bounded sampling period interval. Computer simulation results show the effect of varying the number of discrete states for the HMM and the window width on bandwidth allocation. The results compare favorably with a published approach based on fuzzy logic.
Adaptive congestion control protocol (accp) for wireless sensor networksijwmn
In Wireless Sensor Networks (WSN) when an event is detected there is an increase in data traffic that might
lead to packets being transmitted through the network close to the packet handling capacity of the WSN.
The WSN experiences a decrease in network performance due to packet loss, long delays, and reduction in
throughput. In this paper we developed an adaptive congestion control algorithm that monitors network
utilization and adjust traffic levels and/or increases network resources to improve throughput and conserve
energy. The traffic congestion control protocol DelStatic is developed by introducing backpressure
mechanism into NOAH. We analyzed various routing protocols and established that DSR has a higher
resource congestion control capability. The proposed protocol, ACCP uses a sink switching algorithm to
trigger DelStatic or DSR feedback to a congested node based on its Node Rank. From the simulation
results, ACCP protocol does not only improve throughput but also conserves energy which is critical to
sensor application survivability on the field. Our Adaptive Congestion control achieved reliability, high
throughput and energy efficiency.
Congestion Prediction and Adaptive Rate Adjustment Technique for Wireless Sen...IJORCS
In general, nodes in Wireless Sensor Networks (WSNs) are equipped with limited battery and computation capabilities but the occurrence of congestion consumes more energy and computation power by retransmitting the data packets. Thus, congestion should be regulated to improve network performance. In this paper, we propose a congestion prediction and adaptive rate adjustment technique for Wireless Sensor Networks. This technique predicts congestion level using fuzzy logic system. Node degree, data arrival rate and queue length are taken as inputs to the fuzzy system and congestion level is obtained as an outcome. When the congestion level is amidst moderate and maximum ranges, adaptive rate adjustment technique is triggered. Our technique prevents congestion by controlling data sending rate and also avoids unsolicited packet losses. By simulation, we prove the proficiency our technique. It increases system throughput and network performance significantly.
KALMAN FILTER BASED CONGESTION CONTROLLERijdpsjournal
Facing burst traffic, TCP congestion control algorithms severely decrease window size neglecting the fact
that such burst traffics are temporal. In the increase phase sending window experiences a linear rise which
may lead to waste in hefty proportion of available bandwidth. If congestion control mechanisms be able to
estimate future state of network traffic they can cope with different circumstances and efficiently use
bandwidth. Since data traffic which is running on networks is mostly self-similar, algorithms can take
advantage of self-similarity property and repetitive traffic patterns to have accurate estimations and
predictions in large time scales.
In this research a two-stage controller is presented. In fact the first part is a RED congestion controller
which acts in short time scales (200 milliseconds) and the second is a Kalman filter estimator which do
RTT and window size estimations in large time scales (every two seconds). If the RED mechanism decides
to increase the window size, the magnitude of this increase is controlled by Kalman filter. To be more
precise, if the Kalman filter indicates a non-congested situation in the next large time scale, a magnitude
factor is calculated and given to RED algorithm to strengthen the amount of increase.
Efficient and Fair Bandwidth Allocation AQM Scheme for Wireless NetworksCSCJournals
Heterogeneous Wireless Networks are considered nowadays as one of the potential areas in research and development. The traffic management’s schemes that have been used at the fusion points between the different wireless networks are classical and conventional. This paper is focused on developing a novel scheme to overcome the problem of traffic congestion in the fusion point router interconnected the heterogeneous wireless networks. The paper proposed an EF-AQM algorithm which provides an efficient and fair allocation of bandwidth among different established flows. Finally, the proposed scheme developed, tested and validated through a set of experiments to demonstrate the relative merits and capabilities of a proposed scheme
ANALYSIS OF LINK STATE RESOURCE RESERVATION PROTOCOL FOR CONGESTION MANAGEMEN...ijgca
With the wide spread of WiFi hotspots, concentrated traffic workload on Smart Web (SW) can slow down the network performance. This paper presents a congestion management strategy considering real time activities in today’s smart web. With the SW context, cooperative packet recovery using resource reservation procedure for TCP flows was adapted for mitigating packet losses. This is to maintain data consistency between various access points of smart web hotspot. Using a real world scenario, it was confirmed that generic TCP cannot handle traffic congestion in a SW hotspot network. With TCP in scalable workload environments, continuous packet drops at the event of congestion remains obvious. This is unacceptable for mission critical domains. An enhanced Link State Resource Reservation Protocol (LSRSVP) which serves as dynamic feedback mechanism in smart web hotspots is presented. The contextual behaviour was contrasted with the generic TCP model. For the LS-RSVP, a simulation experiment for TCP connection between servers at the remote core layer and the access layer was carried out while using selected benchmark metrics. From the results, under realistic workloads, a steady-state throughput response was achieved by TCP LS-RSVP to about 3650Bits/secs compared with generic TCP plots in a previous study. Considering network service availability, this was found to be dependent on fault-tolerance of the hotspot network. From study, a high peak threshold of 0.009 (i.e. 90%) was observed. This shows fairly acceptable service availability behaviour compared with the existing TCP schemes. For packet drop effects, an analysis on the network behaviour with respect to the LS-RSVP yielded a drop response of about 0.000106 bits/sec which is much lower compared with the case with generic TCP with over 0.38 bits/sec. The latency profile of average FTP download response was found to be 0.030secs, but with that of FTP upload response, this yielded about 0.028 sec. The results from the study demonstrate efficiency and optimality for realistic loads in Smart web contexts.
Analysis of Link State Resource Reservation Protocol for Congestion Managemen...ijgca
With the wide spread of WiFi hotspots, concentrated traffic workload on Smart Web (SW) can slow down
the network performance. This paper presents a congestion management strategy considering real time
activities in today’s smart web. With the SW context, cooperative packet recovery using resource
reservation procedure for TCP flows was adapted for mitigating packet losses. This is to maintain data
consistency between various access points of smart web hotspot. Using a real world scenario, it was
confirmed that generic TCP cannot handle traffic congestion in a SW hotspot network. With TCP in
scalable workload environments, continuous packet drops at the event of congestion remains obvious. This
is unacceptable for mission critical domains. An enhanced Link State Resource Reservation Protocol (LSRSVP)
which serves as dynamic feedback mechanism in smart web hotspots is presented. The contextual
behaviour was contrasted with the generic TCP model. For the LS-RSVP, a simulation experiment for TCP
connection between servers at the remote core layer and the access layer was carried out while using
selected benchmark metrics. From the results, under realistic workloads, a steady-state throughput
response was achieved by TCP LS-RSVP to about 3650Bits/secs compared with generic TCP plots in a
previous study. Considering network service availability, this was found to be dependent on fault-tolerance
of the hotspot network. From study, a high peak threshold of 0.009 (i.e. 90%) was observed. This shows
fairly acceptable service availability behaviour compared with the existing TCP schemes. For packet drop
effects, an analysis on the network behaviour with respect to the LS-RSVP yielded a drop response of about
0.000106 bits/sec which is much lower compared with the case with generic TCP with over 0.38 bits/sec.
The latency profile of average FTP download response was found to be 0.030secs, but with that of FTP
upload response, this yielded about 0.028 sec. The results from the study demonstrate efficiency and
optimality for realistic loads in Smart web contexts.
Clustering based Time Slot Assignment Protocol for Improving Performance in U...journal ijrtem
Recently, numerous approaches have been proposed for designing medium access control (MAC)
in underwater acoustic networks (UANs). Some of those works tried to adapt MAC protocols proposed for
terrestrial networks. However, unique environmental characteristics of UANs make the MAC protocols hard to be
used in the UANs and degrade network performance. In order to improve network performance, COD-TS MAC
protocol was proposed. COD-TS focuses on both single hop and multi-hop mode and utilizes CDMA for
exchanging schedule information between cluster heads. COD-TS has shortcomings such as collisions, additional
energy consumption by exchanging schedule information and near-far effect of CDMA. To overcome above
shortcomings, we propose a clustering-based time slot assignment protocol. In the proposed protocol, nodes are
clustered, and each cluster head performs two-hop neighbor cluster discovery operation. And then, a cluster head
obtains its own relative position information. Finally, the cluster head assigns its own time slot for data
transmission based on the information. Simulation results show that the proposed protocol has always better
performance compared to the COD-TS.
Clustering based Time Slot Assignment Protocol for Improving Performance in U...IJRTEMJOURNAL
Recently, numerous approaches have been proposed for designing medium access control (MAC)
in underwater acoustic networks (UANs). Some of those works tried to adapt MAC protocols proposed for
terrestrial networks. However, unique environmental characteristics of UANs make the MAC protocols hard to be
used in the UANs and degrade network performance. In order to improve network performance, COD-TS MAC
protocol was proposed. COD-TS focuses on both single hop and multi-hop mode and utilizes CDMA for
exchanging schedule information between cluster heads. COD-TS has shortcomings such as collisions, additional
energy consumption by exchanging schedule information and near-far effect of CDMA. To overcome above
shortcomings, we propose a clustering-based time slot assignment protocol. In the proposed protocol, nodes are
clustered, and each cluster head performs two-hop neighbor cluster discovery operation. And then, a cluster head
obtains its own relative position information. Finally, the cluster head assigns its own time slot for data
transmission based on the information. Simulation results show that the proposed protocol has always better
performance compared to the COD-TS.
Congestion is said to occur in the network when the resource demands exceed the capacity and packets are lost due to too much queuing in the network. During congestion, the network throughput may drop to zero and the path delay may become very high. A congestion control scheme helps the network to recover from the congestion state. In fact, security plays a vital role in Wireless Ad hoc network. This paper presents a systematic literature review to provide comprehensive and unbiased information about various current model Congestion Control conceptions, proposals, problems and solutions in Ad hoc for safety transportation. For this purpose, a total of 33 articles related to the security model in Congestion Control published between 2008 and 2013 were extracted from the most relevant scientific sources (IEEE Computer Society, ACM Digital Library, Springer Link and Science Direct). However, 18 articles were eventually analyzed due to several reasons such as relevancy and comprehensiveness of discussion presented in the articles. Using the systematic method of review, this paper succeeds to reveal the main security threats and Error control, challenges for security, security requirement in Congestion Control in Wireless Ad hoc network (CCWAN) and future research within this scope.
Channel Aware Mac Protocol for Maximizing Throughput and FairnessIJORCS
The proper channel utilization and the queue length aware routing protocol is a challenging task in MANET. To overcome this drawback we are extending the previous work by improving the MAC protocol to maximize the Throughput and Fairness. In this work we are estimating the channel condition and Contention for a channel aware packet scheduling and the queue length is also calculated for the routing protocol which is aware of the queue length. The channel is scheduled based on the channel condition and the routing is carried out by considering the queue length. This queue length will provide a measurement of traffic load at the mobile node itself. Depending upon this load the node with the lesser load will be selected for the routing; this will effectively balance the load and improve the throughput of the ad hoc network.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
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.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...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.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
CONVEX OPTIMIZATION BASED CONGESTION CONTROL IN LAYERED SATELLITE NETWORKS
1. International Journal on Cybernetics & Informatics (IJCI) Vol. 5, No. 1, February 2016
DOI: 10.5121/ijci.2016.5115 157
CONVEX OPTIMIZATION BASED CONGESTION
CONTROL IN LAYERED SATELLITE NETWORKS
R. R. P. Kumar1
, S. Muknahallipatna2
and J. E. McInroy3
1
National Center for Atmospheric Research, Colorado & Univ. of Wyoming, Wyoming
2
Dept. of Electrical & Computer Engineering, University of Wyoming, Wyoming, USA
3
Dept. of Electrical & Computer Engineering, University of Wyoming, Wyoming, USA
ABSTRACT
A multi-layered satellite network consisting of geosynchronous and nano-satellites is suited to perform
space situational awareness. The nano-satellites collect information of space objects and transfer data to
ground stations through the geosynchronous satellites. The dynamic topology of the network, large
propagation delays and bulk data transfers results in a congested network. In this paper, we present a
convex optimization based congestion control algorithm. Using snapshots of the network, operating
parameters such as incoming, outgoing rates and buffer utilization are monitored. The operating
parameters of a satellite are formulated as a convex function and using convex optimization techniques, the
incoming data rates are evaluated to minimize congestion. Performance comparison of our algorithm with
Transmission Control Protocol congestion control mechanism is presented. The simulation results show
that our algorithm reduces congestion while facilitating higher transmission rates.
KEYWORDS
Congestion control, Convex Optimization, Multi-layered satellites.
1. INTRODUCTION
A Single layer satellite networks (SLSN) have the potential to provide global coverage with high
bandwidth availability. SLSN can be used to provide communication infrastructure in remote
areas and allow also interconnection of local area networks and individual hosts. SLSN is highly
reliable due to reduced link failure instances. However, SLSN is shown to be inefficient with
respect to data transmissions [1]. To address this issue, in the past two decades, multi-layered
satellite network (MLSN) has been proposed by a number of researchers [2, 3].
A MLSN consisting of geosynchronous satellites and a large number of nano-satellites with
different capabilities distributed across multiple layers is ideally suited to perform space
situational awareness (SSA). SSA involves collecting visual information of space objects like
stars, planets, satellites etc. SSA using a MLSN involves the use of nano-satellites to collect
visual information and transfer the data to ground stations via multiple geosynchronous satellites
through the layered network in real time. The visual information has dense data transmissions
between satellites. Furthermore, the large physical distances between satellites will result in large
transmission (propagation) delays, causing congestion. Packet drops due to congestion and the
associated re-transmission of dropped packets makes the MLSN unsuitable for real-time SSA.
Hence the need for an algorithm that can reduce the congestion by maintaining maximum
possible data rates is required.
2. International Journal on Cybernetics & Informatics (IJCI) Vol. 5, No. 1, February 2016
158
A number of satellite networks using different flavors of TCP implementations [4] have been
proposed. A number of researchers [5, 6, 7, and 8] have analyzed the reduced throughput of the
TCP based satellite network due to large propagation delay, slow start, packet loss assumption
due to congestion. The packet loss assumption due to congestion will unduly trigger, congestion
control mechanisms resulting in further throughput degradation [9]. A number of modifications to
TCP congestion control mechanism (TCP-CCM) have been proposed in the past two decades [10,
11, 12, 13, 14, and 15]. The first set of modifications proposed, address either preventing
congestion or reduce the congestion rapidly, while a second set of modifications (Fast Retransmit
and Fast Recovery, etc.) focus on detecting whether a packet loss is due to congestion. However,
the throughput of the network continues to be low during the modified congestion control
mechanism operation specifically in satellite networks due to large propagation delay and bulk
data transfers. In this paper, we propose a convex optimization based congestion control (COCC)
algorithm that uses convex optimization to reduce congestion and achieve a maximal network
throughput.
Three important parameters that contribute to congestion in a satellite network are the input
buffer size, incoming and outgoing data rates of each satellite. The input buffer size and the
incoming data rates determine the effectiveness of receiving data. The outgoing data rate
determines the effectiveness of processing the received transmission and relaying it to the next
satellite in the chain of communication links. An imbalance in the parameters can result in a
satellite receiving more data than it can process, leading to congestion. The proposed algorithm
consists of formulating the input buffer utilization and the incoming data rate as a convex
function. Convex optimization is used to solve this convex function with associated constraints to
determine the maximal possible throughput of each satellite and thereby reduce network
congestion.
The paper is organized as follows: In section 2, we discuss the related work on congestion control
in multi-layered satellite networks. Section 3 presents the multi-layered satellite network
architecture. Section 4 provides a brief discussion of the parameters that influence congestion. In
section 5, we present the traditional TCP modeling that is used for comparison. Section 6 presents
the formulation of congestion control as a convex function. Section 7 presents an introduction to
convex optimization and its application to congestion control. Simulation and performance
evaluation of the proposed algorithm is presented in Section 8 by comparing the performance
with traditional TCP-CCM. Section 9 concludes with discussion on performance issues of the
COCC algorithm.
2. RELATED WORK
A QoS oriented congestion control algorithm is proposed for satellite networks in [16]. A satellite
node utilizes an equation to compute the sending rate for each data flow, while the intermediate
satellite nodes continuously detect real-time package-loss rates for timely adjustments. Simulation
results indicate that the algorithm can provide superior congestion control performance, and raise
network throughputs without reducing the QoS. However, the equation used to compute the
sending rate for each data flow does not optimize the network throughput. Neither does it provide
any flexible control mechanism to control source or intermediate satellite nodes to modulate
sending rates. Moreover, effects of the algorithm for a multi-layered satellite network are not
presented.
Congestion control using an optimized load-balancing traffic distribution algorithm for two-
layered satellite network is proposed in [17]. The load-balancing scheme of the proposed method
is developed by adopting a traffic distribution model, which is based upon network capacity
estimation and theoretical analysis of the congestion rate in each layer. When congestion is
3. International Journal on Cybernetics & Informatics (IJCI) Vol. 5, No. 1, February 2016
159
detected, the routing tables of satellites are modified to avoid the congested nodes. The
performance of this method is effective in terms of improved throughput and lower packet drops.
Congestion control for a multi-layered satellite network in [18] is based on the probability of
packet drop. Queuing ratios of satellites are varied based on the probability of packet drops at the
given instance of time. This determines the traffic reduction ratio. New transmission rates are
computed using the ratio that reduces congestion.
A congestion control algorithm based on sudden start and rapid recovery algorithm is introduced
in [19]. The sudden start increases the transmission window size rapidly. Probe packets are
transmitted periodically to check for congestion. On congestion, the rapid recovery phase
algorithm cuts the window size by half for every lost packet. The performance shows higher
network throughput and better fairness in sharing network resources in comparison to TCP-CCM.
The limitation of the algorithm is the additional data overhead due to the probe packets.
Multilayer multicast congestion control algorithm is introduced in [20]. The satellites are grouped
to retrieve session information from the ongoing traffic. The routing is computed based on the
session information. Additionally, every packet is marked with priorities by every layer. Packets
of lower priority are blocked during congestion and released after recovery. The algorithm has the
advantage of being reliable in case of link failures, long and variable delays, limited control
overhead and fair sharing of network resources.
Congestion control algorithm for lower earth orbit satellites is introduced in [21]. The round trip
time (RTT) for any transmission is estimated. For a given route, the satellites are grouped based
on the same number of hops and RTT. A feedback window is multicast once for every RTT to
avoid congestion. The algorithm requires no modifications to a router or end-user. The
performance indicates better load balancing and link utilization than traditional congestion control
algorithms.
A fuzzy logic based congestion control algorithm is introduced in [22]. The algorithm formulates
congestion as a function of queuing and weather characteristics. The history of weather changes
and queuing for every satellite is maintained. The algorithm then computes fuzzy logic table
providing the probable values of these variables. This helps in tuning of Random Early Detection
(RED) algorithm. The performance of the algorithm is shown to be better than the traditional
RED algorithm.
A congestion controller using data-driven switching control theory is introduced in [23, 24]. A
control scheme of proportional integral-derivative structure is used to represent the congestion in
networks. The controller monitors the network for any congestion. A cost function is designed to
evaluate control parameters for the controller. The parameters deduced show that the algorithm is
computationally less intensive than most common algorithms making it suitable for real time
applications.
A study on the set of guidelines governing satellite queuing system is provided in [25]. It provides
a fair routing algorithm that selectively drops packets to reduce congestion. The algorithm
discriminates packets that impose bandwidth more than their allocation. This discrimination
enables the satellite to drop the right packets during congestion. The performance is shown to be
better than traditional congestion control algorithms through simulations. However, Huang et al
state in [25] that the implementation on a satellite network may not be feasible.
4. International Journal on Cybernetics & Informatics (IJCI) Vol. 5, No. 1, February 2016
160
3. MOTIVATION
As mentioned before, SSA using MLSN involves a large number of nano-satellites, with each
satellite involving dense data transmissions. Furthermore, a real-time SSA using MLSN would
require to have maximum feasible network throughput, even during congestion phase.
In all of the previous work discussed, the congestion is reduced by reducing the transmission rate
either linearly or exponentially without any consideration to the network throughput. The review
of congestion control algorithms in [26] shows the same. Our proposed algorithm differs
significantly by adopting a different goal for congestion control. The goal is to clear congestion
while maintaining maximal network throughput. To achieve this goal, congestion control is
formulated as a convex function with incoming data rates of each satellite as the variable of
optimization. It reduces congestion and optimizes the data flow simultaneously, providing an
efficient network throughput.
4. ARCHITECTURE
A novel multi-layered satellite routing algorithm is proposed in [27]. The proposed routing
algorithm performance is demonstrated on a satellite network consisting of satellites distributed
over multiple layers with an individual layer situated either at lower earth orbit (LEO) or middle
earth orbit (MEO) or geosynchronous earth orbit (GEO). The performance of the network in [27]
is shown to have low communication overhead and better throughput than other fewer-layered
satellite networks. However, the focus of this work is only on optimal routing and does not
address the issues with congestion and maximal network throughput. In this work, we
demonstrate our convex optimization based congestion control algorithm on the satellite network
test bed, which is a modified version of the layered satellite network architecture proposed in
[27]. The modifications are the LEO and the MEO layers, are referred to as layer-1 and layer-2
respectively, comprising of only nano-satellites. Layer-1 and layer-2 are not expected to be
situated at the low and medium earth orbits. The GEO layer is referred as layer-3 consisting of
GEO satellites capable of communicating with the ground stations. The communication
(transmission and reception rates) capabilities of satellites are assumed to increase from layer-1
through layer-3. Satellites are assumed to communicate within and between layers via intra-
orbital and inter-orbital links respectively. It is assumed that every satellite knows its position via
geographic coordinate system. The hierarchy of the satellites is shown in Fig 1.
Let the number of GEO satellites be GN , number of layer-2 satellites be MN and number of
layer-1 satellites be LN . The satellites are represented by
Gi NigG ,...,2,1| (1)
},...,2,1|{ Mj NjmM (2)
},...,2,1|{ Lk NklL (3)
where, ig , kj lm , represent the individual layer-3, layer-2 and layer-1 satellites respectively. As
seen in Fig. 1, layer-1 has two sub-layers deviating from the architecture proposed in [27]. In
order to efficiently maintain data flow between satellites, manager or cluster head (CH) satellites
are introduced.
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The individual satellite naming convention used in identifying the data flow or links is discussed
below:
For layer-1, satellite links have two representations, hkl , and h
jkl , , where hkl , is the link
between th
k non-cluster head satellite in layer-1 and CH satellite h of layer-1. h
jkl , is the
satellite link between th
k CH satellite in layer-1 to the th
j satellite in layer-2.
Satellites ( ijm , ) in layer-2 are arranged in a single orbit, where j is the identifier of a
satellite in layer-2 and i is the identifier of a satellite in layer-3.
Layer-3 will have satellites that may or may not have ground connectivity. The satellites
having connectivity to a ground station are selected as cluster heads. The two identifiers
of satellite links in this layer are hig , and h
ig . hig , is the link between th
i satellite and CH
satellite of layer-3. h
ig is the link between the ith
CH in layer-3 to the ground station.
Fig. 1. Hierarchy of the Multi-layered Satellite Network
The data collected by hkl , is transmitted to h
jkl , . Each h
jkl , routes this data to ijm , , which further
routes it to either hig , or h
ig . The hig , relays their data to h
ig , and eventually data to the ground
stations.
5. CONGESTION CONTROL PARAMETERS
Due to the dynamic topology of a satellite network, the parameters like propagation delay,
maximum possible data rates, etc., change within a well-defined bandwidth. However, these
parameters can be assumed to be constant within a snapshot. A snapshot is defined as a brief
period of time and in which the network topology change is minimal. A snapshot approach is
useful in analyzing the current state of a dynamic network, and determines the operational
parameters of the network for the next state. At the beginning of every snapshot, every satellite
ji mg , and kl based on their current position, will compute the following three parameters:
Line of sight with other satellites,
Maximum data transmission rates
Data recipients
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5.1. Line of Sight
The inter-orbital and intra-orbital links being wireless require a LOS for transmission. The
satellites using the geographical coordinate system will determine the LOS satellites as discussed
in [28, 29]. To determine LOS, position vectors of a satellite and difference vectors are used. A
position vector of a satellite is the Euclidean vector representing the position of the satellite with
the center of the earth as its origin. A difference vector is the Euclidean vector obtained by the
subtraction of two Euclidean vectors. Using these vectors, LOS is computed as follows:
Let 1 represents the angle between satellite A’s position vector and the difference vector
(difference between A and B satellites’ position vector).
Let 2 represents the angle between satellite B’s position vector and the difference vector.
A LOS exists between A and B if any of the following conditions is satisfied:
901
901 and
902
901 ,
902 and the orthogonal from the center of the earth to the line joining the
two satellites is greater than the radius of the earth.
5.2. Maximum Data Transmission Rates
Once the LOS between two satellites is determined, the satellites are considered as neighbors.
Laser transmission is assumed as the mode of communication in this work to achieve high
transmission rates. Laser transmission rate is dependent on a number of parameters [30] like
transmission power, area of transmitter antenna, distance between satellites, etc. For a given laser
communication configuration, the relationship between maximum data transmission rate and the
distance between two satellites can be expressed as
2max
1
D
R (4)
where,
D is the distance between the two satellites.
D varies between satellites in different layers constantly due to their orbital locations. The
transmission rate of a transmitting satellite is the arrival rate at the receiving satellite. Even
though, maxR is the maximum possible transmission rate of a satellite in a snapshot, the actual
transmission rate will be dictated by the underlying TCP.
5.3. Data Recipients
A top down approach is adopted to select the data recipients at each layer. The notations and data
flow for the network is as shown in Fig. 2. CH satellites are primarily chosen based on LOS.
Satellites that do not have a LOS with a CH in a snapshot, do not participate in any transmission
activity. Satellites having LOS to multiple CHs can choose to transmit to any or all of them.
CH h
ig is chosen based on its connectivity to a ground station. CH h
jkl , is chosen based on greedy
algorithm of maximum neighboring kl satellites. From a set of kl satellites having a ijm ,
neighbor, a satellite in the set with maximum number of neighboring kl is chosen as a CH.
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Fig. 2. Data flow in the Multi-Layered Satellite Network
6. TCP MODELLING
In this work, the TCP flavor described in [31] has been adopted for comparison with the convex
optimization based congestion control algorithm.
At the beginning of every snapshot, the satellites resume transmission activity based on the
computed hierarchy of transmission. The allocated rate of transmission allocR , governed by TCP,
will be a fraction of maxR as given in Eq. 5
maxRTR tcpalloc (5)
where, tcpT is the a threshold satisfying Eq. 6
10 tcpT (6)
The threshold tcpT varies based on the success or failure of every transmission. In every snapshot,
the satellites follow the TCP principles i.e., slow start or exponential growth phase below a preset
TCP transmission rate and a linear growth thereafter. The linear growth is continued till
congestion is detected or tcpT reaches unity. If congestion is detected, the transmission is subjected
to the TCP-CCM where the slow start window is cut by half and slow start is restarted. Once the
congestion is cleared, the TCP resumes back its transmission with linear growth. If no congestion
is detected, the transmission rate is maintained at maxR . Furthermore, the satellites are allowed to
transmit data in bursts. The amount of data a satellite can transmit in bursts is limited by the
bandwidth-delay product [32].
7. FORMULATION OF CONGESTION CONTROL AS CONVEX FUNCTION
Let the service rate of packets of a satellite be . Let the maximum arrival rate of packets on an
th
i input link of a satellite be i . In order to empty the buffer, and thus reduce congestion, the
service rate and the arrival rates must satisfy the relation:
n
i
i
1
(7)
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where, n indicates the number of satellites transmitting. At
n
i
i
1
, the network is said to be at
a critical state indicating that the buffer is always empty. For any satellite with buffer capacity B ,
Eq. 7 can be re-written as:
n
i
utili BB
1
(8)
where,
10 utilB .
The product BButil represents buffer utilization. If the data rates in Eq. 8 are optimized, a network
will operate with minimal congestion and maximal throughput.
Let nn
RR max be maximum transmission rates of all satellites transmitting to a single CH satellite:
n
n
R 21max (9)
where, n is the number of incoming links of a CH satellite. In order to find an effective data rate
satisfying the condition of minimum queuing delay, a scalar multiple for each i has to be
considered. The collection of scalar multiples is represented as nwwwW 21 , where
10 iw , such that:
BBWR util
Tn
max (10)
Eq. 10 is a linear equation of n
RW . Next, we will show Eq. 10 to be a convex function.
8. CONVEX OPTIMIZATION AND APPLICATION TO CONGESTION CONTROL
A set S , is defined as convex if and only if it satisfies the condition [33] described in Eq. 11.
Sxx 21 1 (11)
where,
Sxx 21, ,
21 xx ,
R , and
10 .
A function RRXf n
:)( is considered convex [33] if and only if for all fdomainXX 21,
satisfies Eq. 12.
2121 11 XfXfXXf (12)
Consider the inequality,
bXaT
(13)
where,
n
Ra ,
Rb , and
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n
RX is the unknown to be determined.
Eq. 13 represents a linear inequality in n-dimensional half-space with multiple solutions. X is a
convex set since it satisfies Eq. 11 and therefore is a solution of Eq. 13 for a given ba, . S. Boyd
and L. Vanderberghe have shown linear functions to be convex functions [33].Comparing Eq. 10
and Eq. 13, it can be seen that Tn
Rmax and BButil are T
a and b respectively, thereby Eq.
10 is a convex function and a linear inequality.
Eq. 10 or Eq. 13 can also be solved using a simplex algorithm. Simplex algorithms are infeasible
for large data [34]. For SSA using MLSR, a large number of nano-satellites are involved. Hence,
in Eq. 10, as n grows large, simplex algorithm becomes infeasible. Furthermore, simplex
algorithm optimizes linear functions only. Convex optimization can be applied on a convex
function which can be linear, quadratic or geometric. Hence, optimizing congestion control
formulated as a convex function allows future work to add additional parameter or constraints to
congestion control for different or complex networks.
Any standard convex optimization toolkit can be used to solve Eq. 10. To obtain the global
minima and in this work, the CVX toolkit [33] developed by S. Boyd and L. Vanderberghe for
implementing convex optimization in Matlab is used. To solve a convex function, this toolkit
requires the convex function to be specified in a particular format. The toolkit requires objective
variable and convex constraints to solve the optimization problem. The objective in the
congestion control problem is optimizing W which is n-dimensional. However, the toolkit allows
the objective to be only a single dimension variable. Therefore, a variable is introduced which
will be maximized for each satellite as shown in Eq. 14.
subject to
maximize
BBWR util
Tn
max
10 iw
iiiw
iiiw
iw
(14)
where,
i , i are the lower and upper limits of the ith
incoming link rate.
Since faces the constraint iw , in-turn, all elements of iw are maximized. The constraint
10 iw forces iw to be a convex set. The other two constraints are to enforce the effective
incoming link rate is maintained within a bandwidth. The advantage of convex optimization is
observed in these two constraints. It facilitates to optimize transmission rates within the desired
bandwidth which would not be possible if least squares technique was used.
The COCC algorithm on a CH satellite is triggered when the effective buffer utilization is within
the bounds defined by upperlower BB , . Therefore, the COCC algorithm is activated at
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upperutil BBB and deactivated at lowerutil BBB . Once the COCC phase ends, TCP-CCM regains
control of the transmission.
A CH after computing the optimal transmission rates ii w for its incoming links, relays these
desired rates to all of its neighboring satellites and this process is repeated on all congested CH
satellites.
9. SIMULATIONS AND ANALYSIS
The simulations are tailored to evaluate performance of COCC in comparison to TCP. The
comparison is performed by considering two parameters namely:
Average Buffer utilization of a Layer: Average Buffer Utilization is defined as the average of
the buffer utilization of each CH satellite in a layer for a snapshot.
Average Link utilization of a Layer: Average Link Utilization is defined as the average of the
link utilization of each satellite in a layer for a snapshot.
Simulations are performed with 135 satellites distributed across the three layers in the ratio of
1:4:40. Layer-1 contains 120 satellites distributed in orbits with altitude ranging from 28,000 km
to 32,500 km. Layer-2 contains 12 satellites distributed in orbits with altitude ranging from
33,000 km to 35,000 km. Layer-3 contains 3 satellites in the geosynchronous orbit. Based on the
above satellite distribution, the average theoretical data rates for a CH satellite in layer-1, layer-2
and layer-3 was 1 Mbps, 10 Mbps and 8 Mbps respectively. The layer-1 theoretical data rate is
significantly less compared to layer-2 theoretical data rate due to a smaller antenna with lower
transmission capability. Layer-3 theoretical data rate is also lower compared to layer-2 theoretical
data rate due to the large distance between geosynchronous satellites and ground stations and the
effect of earth’s atmosphere on laser transmission. The buffer size of each satellite in layer-1,
layer-2 and layer-3 were set to 1 MB, 1 GB and 10MB respectively. The buffer size on a
geosynchronous satellite was set to a lower value to increase the effect of congestion. Initially,
simulations were performed with a 30 second snapshot intervals. Since our proposed algorithm
works only on network layer, the network flow for duration of 30 minutes was simulated using
the CVX toolkit on Matlab and Satellite ToolKit (STK). The simulation results presented are
based on 10 trials. The standard deviation from the 10 trials for average buffer utilization and
average link utilization vary from 3.7% to 6.7% across the layers.
In Figs. 3, 4 and 5 the average buffer utilization for layers 3, 2 and 1 are shown respectively. In
Figs. 6, 7 and 9 the corresponding average link utilization for layers 3, 2 and 1 are shown
respectively.
Fig. 3. Layer-3 Average Buffer Utilization for TCP-CCM and COCC
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Fig. 4. Layer-2 Average Buffer Utilization for TCP-CCM and COCC
Fig. 5. Layer-1 Average Buffer Utilization for TCP-CCM and COCC
Fig. 6. Layer-3 Average Link Utilization for TCP-CCM and COCC
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Fig. 7. Layer-2 Average Link Utilization for TCP-CCM and COCC
Fig. 8. Layer-1 Average Link Utilization for TCP-CCM and COCC
In Fig. 3 the average buffer utilization of satellites in layer-3 with traditional TCP-CCM is above
100% on an average for the entire simulation. This indicates significant number of packets being
dropped. However, with the COCC algorithm on an average, the buffer utilization is around
100%. Since the buffer utilization at layer-3 with TCP-CMM is above 100%, the corresponding
average link utilization is less than 80% for satellites in layer-2 as seen in Fig. 7. However, with
COCC algorithm, the average link utilization for the same satellites in layer-2 is close to 90% due
to buffer utilization reduction in layer-3. In Fig. 4, the buffer utilization with TCP-CCM or
COCC is negligible compared to other layers. This is due to the satellites in this layer having
higher theoretical transmission rate, larger buffer size and experiencing a lower input data rate
from CHs in layer-1. It was observed due to the layer-2 and layer-1 orbit altitudes, in any given
snapshot, a total of 30 satellites among the 120 satellites in layer-1 were chosen as CHs. Hence
each CH in layer-1 is servicing a maximum of 3 non-CH satellites. Therefore the average buffer
utilization of the CHs in layer-1 is only around 20% for both TCP-CCM and COCC as seen in
Fig. 5. Since the ground stations do not experience any congestion in our simulations, the link
utilization in layer-3 is high as seen in Fig. 6. The link utilization of layer-1 satellites is not
affected by the buffer utilization in layer-2. The link utilization with TCP-CCM in layer-1 is less
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compared to that with COCC as seen in Fig. 8. This is due to the use of slow start and congestion
avoidance by TCP-CCM at the start of a new snapshot.
Even though COCC performs better congestion control it still has some limitations. One of the
limitation is the lethargic congestion control at activation of COCC. When COCC is activated on
a congested CH satellite, the new transmission rates to reduce congestion is computed and
transmitted on all its incoming links with a delay. Due to this delay, the buffer utilization is still
shooting above 100% in Fig. 3. This limitation can be overcome by allowing COCC a continuous
control over congestion control mechanism. However, allowing COCC to perform continuous
congestion control imposes a large computational burden as shown in Fig. 11. To avoid this
computational burden, instead of allowing COCC to perform continuous congestion control we
have explored varying the duration of a snapshot. In Fig. 9, the buffer utilization with snapshot
durations of 30 and 15 seconds are shown. It can be seen the buffer utilization not exceeding
100% with 15 seconds snapshot and thereby no packets are dropped resulting in high link
utilization as seen in Fig. 10.
As previously mentioned, the other limitation is the computational burden of COCC. The
computation time of COCC is dependent on parameters such as number of neighboring satellites,
snapshot interval, data transmission rates, iterations involved in convex optimization etc. For a
30s snapshot interval executed on a Quad-core desktop, an average computation time was 3.25
minutes with 50 satellites as shown in Fig. 11. It can also be noticed that the computational time
increases linearly with increasing number of satellites. At this stage due to the computational
burden COCC is not suitable for real-time application.
Fig. 9. Layer-3 Average Buffer Utilization for varied Snapshot Interval
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Fig. 10. Layer-3 Average Link Utilization for varied Snapshot Interval
Fig. 11. New Data Rates Computation Time with COCC
10. CONCLUSIONS
The paper proposes a new congestion control algorithm for layered satellite networks. The
approach is to formulate congestion control as a convex optimization problem. The convex
function is optimized using convex optimization approach at discrete intervals of time to
determine optimal transmission rate of each satellite such that the network congestion is reduced
while maintaining optimal network throughput. The performance of COCC was compared with
TCP-CCM and the performance of COCC is better. It was observed that the satellites transmitted
higher transmission rates with COCC algorithm. Furthermore, the performance of COCC is
improved when the snapshot duration is reduced. Currently, a constant control by COCC is not
feasible due to large computational burden.
To use COCC algorithm in real-time, the COCC algorithm needs to be executed in parallel for
each satellite necessitating parallelization of the CVX toolkit.
ACKNOWLEDGEMENTS
We would like to thank National Center for Atmospheric Research, Boulder, for providing
resources.
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