The paper presents a Riverbed simulator implementation with both routing and medium access control
(MAC) protocols for mobile ad-hoc network wireless networks with multi-beam smart antennas (MBSAs).
As one of the latest promising antenna techniques, MBSAs can achieve concurrent transmissions /
receptions in multiple directions/beams. Thus it can significantly improve the network throughput.
However, so far there is still no accurate network simulator that can measure the MBSA-based
routing/MAC protocol performance. In this paper, we describe the simulation models with the
implementation of MBSA antenna model in physical layer, MAC layer, and routing layer protocols, all in
Riverbed Modeler. We will compare two routing scenarios, i.e., multi-hop diamond routing scenario and
multi-path pipe routing. We will analyze the network performance for those two scenarios and illustrate the
advantages of using MBSAs in wireless networks.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel Multi-
Radios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
INVESTIGATING MULTILAYER OMEGA-TYPE NETWORKS OPERATING WITH THE CUT-THROUGH T...IJCNCJournal
The continuous increase in the complexity of data networks has motivated the development of more effective Multistage Interconnection Networks (MINs) as important factors in providing higher data transfer rates in various switching divisions. In this paper, semi-layer omega-class networks operating with a cut-through forwarding technique are chosen as test-bed subjects for detailed evaluation, and this network architecture is modelled, inspected, and simulated. The results are examined for relevant singlelayer omega networks operating with cut-through or ‘store and forward’ forwarding techniques. Two series of experiments are carried out: one concerns the case of uniform traffic, while the other is related to hotspot traffic. The results quantify the way in which this network outperforms the corresponding singlelayer network architectures for the same network size and buffer size. Furthermore, the effects of the dimensions of the switch elements and their corresponding reliability on the overall interconnection system are investigated, and the complexity and the relevant cost are examined. The data yielded by this investigation can be valuable to MIN engineers and can allow them to achieve more productive networks with lower overall implementation costs.
JOINT-DESIGN OF LINK-ADAPTIVE MODULATION AND CODING WITH ADAPTIVE ARQ FOR COO...IJCNCJournal
This paper analyzes the efficiency of a joint-design of an adaptive modulation and coding (AMC) at the
physical (PHY) layer with an adaptive Rmax-truncated selective-repeat automatic repeat request (ARQ)
protocol at the medium access control (MAC) layer to maximize the throughput of cooperative nonregenerative
relay networks under prescribed delay and/or error performance constraints. Particularly, we
generalize the existing design model/results for cross-layer combining of AMC along with truncated ARQ
in non-cooperative diversity networks in three-folds: (i) extension of the cross-layer PHY/MAC design or
optimization to cooperative diversity systems; (ii) generalization/unification of analytical expressions for
various network performance metrics to generalized block fading channels with independent but nonidentically
distributed (i.n.d) fading statistics among the spatially distributed nodes; (iii) analysis of the
effectiveness of joint-adaptation of the maximum retransmission limit Rmax of ARQ protocol and
cooperative diversity order N for delay-insensitive applications. Our insightful numerical results reveal
that the average throughput can be increased significantly by judiciously combining two additional degrees
of freedom (N and Rmax) that are available in cooperative amplify-and-forward (CAF) relay networks
besides employing AMC at the PHY layer, especially in the most challenging low signal-to-noise ratio
(SNR) regime.
With the increase of usage of wireless networks for purposes where the nodes are either stationary or minimally mobile, focus is also on increasing the network capacity of wireless networks. One such way is to use non-overlapping multiple channels provided by 802.11 by using multiple interfaces per node. Multiple non overlapped channels exist in the 2.4 GHz and 5 GHz spectrum. Under this scenario, several challenges need to be addressed before all the available channels can be fully utilized.
AN EFFECTIVE CONTROL OF HELLO PROCESS FOR ROUTING PROTOCOL IN MANETSIJCNCJournal
In the mobile ad hoc network (MANET) update of link connectivity is necessary to refresh the neighbor tables in data transfer. A existing hello process periodically exchanges the link connectivity information, which is not adequate for dynamic topology. Here, slow update of neighbour table entries causes link failures which affect performance parameter as packet drop, maximum delay, energy consumption, and reduced throughput. In the dynamic hello technique, new neighbour nodes and lost neighbour nodes are used to compute link change rate (LCR) and hello-interval/refresh rate (r). Exchange of link connectivity information at a fast rate consumes unnecessary bandwidth and energy. In MANET resource wastage can be controlled by avoiding the re-route discovery, frequent error notification, and local repair in the entire network. We are enhancing the existing hello process, which shows significant improvement in performance.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel Multi-
Radios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
INVESTIGATING MULTILAYER OMEGA-TYPE NETWORKS OPERATING WITH THE CUT-THROUGH T...IJCNCJournal
The continuous increase in the complexity of data networks has motivated the development of more effective Multistage Interconnection Networks (MINs) as important factors in providing higher data transfer rates in various switching divisions. In this paper, semi-layer omega-class networks operating with a cut-through forwarding technique are chosen as test-bed subjects for detailed evaluation, and this network architecture is modelled, inspected, and simulated. The results are examined for relevant singlelayer omega networks operating with cut-through or ‘store and forward’ forwarding techniques. Two series of experiments are carried out: one concerns the case of uniform traffic, while the other is related to hotspot traffic. The results quantify the way in which this network outperforms the corresponding singlelayer network architectures for the same network size and buffer size. Furthermore, the effects of the dimensions of the switch elements and their corresponding reliability on the overall interconnection system are investigated, and the complexity and the relevant cost are examined. The data yielded by this investigation can be valuable to MIN engineers and can allow them to achieve more productive networks with lower overall implementation costs.
JOINT-DESIGN OF LINK-ADAPTIVE MODULATION AND CODING WITH ADAPTIVE ARQ FOR COO...IJCNCJournal
This paper analyzes the efficiency of a joint-design of an adaptive modulation and coding (AMC) at the
physical (PHY) layer with an adaptive Rmax-truncated selective-repeat automatic repeat request (ARQ)
protocol at the medium access control (MAC) layer to maximize the throughput of cooperative nonregenerative
relay networks under prescribed delay and/or error performance constraints. Particularly, we
generalize the existing design model/results for cross-layer combining of AMC along with truncated ARQ
in non-cooperative diversity networks in three-folds: (i) extension of the cross-layer PHY/MAC design or
optimization to cooperative diversity systems; (ii) generalization/unification of analytical expressions for
various network performance metrics to generalized block fading channels with independent but nonidentically
distributed (i.n.d) fading statistics among the spatially distributed nodes; (iii) analysis of the
effectiveness of joint-adaptation of the maximum retransmission limit Rmax of ARQ protocol and
cooperative diversity order N for delay-insensitive applications. Our insightful numerical results reveal
that the average throughput can be increased significantly by judiciously combining two additional degrees
of freedom (N and Rmax) that are available in cooperative amplify-and-forward (CAF) relay networks
besides employing AMC at the PHY layer, especially in the most challenging low signal-to-noise ratio
(SNR) regime.
With the increase of usage of wireless networks for purposes where the nodes are either stationary or minimally mobile, focus is also on increasing the network capacity of wireless networks. One such way is to use non-overlapping multiple channels provided by 802.11 by using multiple interfaces per node. Multiple non overlapped channels exist in the 2.4 GHz and 5 GHz spectrum. Under this scenario, several challenges need to be addressed before all the available channels can be fully utilized.
AN EFFECTIVE CONTROL OF HELLO PROCESS FOR ROUTING PROTOCOL IN MANETSIJCNCJournal
In the mobile ad hoc network (MANET) update of link connectivity is necessary to refresh the neighbor tables in data transfer. A existing hello process periodically exchanges the link connectivity information, which is not adequate for dynamic topology. Here, slow update of neighbour table entries causes link failures which affect performance parameter as packet drop, maximum delay, energy consumption, and reduced throughput. In the dynamic hello technique, new neighbour nodes and lost neighbour nodes are used to compute link change rate (LCR) and hello-interval/refresh rate (r). Exchange of link connectivity information at a fast rate consumes unnecessary bandwidth and energy. In MANET resource wastage can be controlled by avoiding the re-route discovery, frequent error notification, and local repair in the entire network. We are enhancing the existing hello process, which shows significant improvement in performance.
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.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
Performance Analysis of Mesh-based NoC’s on Routing Algorithms IJECEIAES
The advent of System-on-Chip (SoCs), has brought about a need to increase the scale of multi-core chip networks. Bus Based communications have proved to be limited in terms of performance and ease of scalability, the solution to both bus – based and Point-to-Point (P2P) communication systems is to use a communication infrastructure called Network-on-Chip (NoC). Performance of NoC depends on various factors such as network topology, routing strategy and switching technique and traffic patterns. In this paper, we have taken the initiative to compile together a comparative analysis of different Network on Chip infrastructures based on the classification of routing algorithm, switching technique, and traffic patterns. The goal is to show how varied combinations of the three factors perform differently based on the size of the mesh network, using NOXIM, an open source SystemC Simulator of mesh-based NoC. The analysis has shown tenable evidence highlighting the novelty of XY routing algorithm.
An Efficient System for Traffic Control in Networks Using Virtual Routing Top...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
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.
DISTRIBUTED TRAFFIC BY LOAD-BALANCING APPROACH FOR AOMDV IN AD-HOC NETWORKScscpconf
Mobile ad hoc network is a collection of wireless mobile nodes, which are connected over a wireless medium. There is no pre-existing communication infrastructure (no access points, no
base stations) and the nodes can freely move and self-organize into a network topology. Such a network can contain two or more nodes. Hence, balancing the load in an Ad hoc network is
important because the nodes have limited communication resources such as bandwidth, buffer space and battery power. This paper presents a new approach to load balancing based on
residual energy of nodes for distribute the traffic evenly among the network nodes. We are exploiting the multipath routing protocol AOMDV, which defines link-disjoint paths between the
source and the destination in every route discovery. We add the energy metric for load balancing (ELB-AOMDV). The performance is compared between ELB-AOMDV and LBAOMDV.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
GPSFR: GPS-Free Routing Protocol for Vehicular Networks with Directional Ante...ijwmn
Efficient and practical communications between large numbers of vehicles are critical in providing high level of safety and convenience to drivers. Crucial real-time information on road hazard, traffic conditions and driver services must be communicated to vehicles rapidly even in adverse environments, such as “urban canyons” and tunnels. We propose a novel routing protocol in vehicular networks that does not require position information (e.g. from GPS) but instead rely on relative position that can be determined dynamically. This GPS-Free Geographic Routing (GPSFR) protocol uses the estimated relative position of vehicles and greedily chooses the best next hop neighbor based on a Balance Advance (BADV) metric which balances between proximity and link stability in order to improve routing performance. In this paper, we focuses primarily on the complexity of routing in highways and solves routing problems that arise when vehicles are near interchanges, curves, and merge or exit lanes of highways. Our simulation results show that by taking relative velocity into account, GPSFR reduces link breakage to only 27% that of GPSR in the dense network. Consequently, GPSFR outperforms GPSR in terms of higher data delivery ratio, lower delay, less sensitivity of the network density and route paths’length
Cooperative load balancing and dynamic channel allocation for cluster based m...ieeeprojectschennai
Cooperative load balancing and dynamic channel allocation for cluster based mobile ad hoc networks
+91-9994232214,8144199666, ieeeprojectchennai@gmail.com,
www.projectsieee.com, www.ieee-projects-chennai.com
IEEE PROJECTS 2015-2016
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Contact:+91-9994232214,+91-8144199666
Email:ieeeprojectchennai@gmail.com
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RIVERBED-BASED NETWORK MODELING FOR MULTI-BEAM CONCURRENT TRANSMISSIONSijwmn
The paper presents a Riverbed simulator implementation with both routing and medium access control (MAC) protocols for mobile ad-hoc network wireless networks with multi-beam smart antennas (MBSAs). As one of the latest promising antenna techniques, MBSAs can achieve concurrent transmissions /
receptions in multiple directions/beams. Thus it can significantly improve the network throughput. However, so far there is still no accurate network simulator that can measure the MBSA-based
routing/MAC protocol performance. In this paper, we describe the simulation models with the implementation of MBSA antenna model in physical layer, MAC layer, and routing layer protocols, all in Riverbed Modeler. We will compare two routing scenarios, i.e., multi-hop diamond routing scenario and multi-path pipe routing. We will analyze the network performance for those two scenarios and illustrate the advantages of using MBSAs in wireless networks.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM) ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
A Flexible Software/Hardware Adaptive Network for Embedded Distributed Archit...csijjournal
Embedded platforms are projected to integrate hundreds of cores in the near future, and expanding the interconnection network remains a key challenge. We propose SNet, a new Scalable NETwork paradigm that extends the NoCs area to include a software/hardware dynamic routing mechanism. To design routing pathways among communicating processes, it uses a distributed, adaptive, non-supervised routing method based on the ACO algorithm (Ant Colony Optimization). A small footprint hardware unit called DMC speeds up data transfer (Direct Management of Communications). SNet has the benefit of being extremely versatile, allowing for the creation of a broad range of routing topologies to meet the needs of various applications. We provide the DMC module in this work and assess SNet performance by executing a large number of test cases.
A FLEXIBLE SOFTWARE/HARDWARE ADAPTIVE NETWORK FOR EMBEDDED DISTRIBUTED ARCHIT...csijjournal
Embedded platforms are projected to integrate hundreds of cores in the near future, and expanding the
interconnection network remains a key challenge. We propose SNet, a new Scalable NETwork paradigm
that extends the NoCs area to include a software/hardware dynamic routing mechanism. To design routing
pathways among communicating processes, it uses a distributed, adaptive, non-supervised routing method
based on the ACO algorithm (Ant Colony Optimization). A small footprint hardware unit called DMC
speeds up data transfer (Direct Management of Communications). SNet has the benefit of being extremely
versatile, allowing for the creation of a broad range of routing topologies to meet the needs of various
applications. We provide the DMC module in this work and assess SNet performance by executing a large
number of test cases.
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.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
Performance Analysis of Mesh-based NoC’s on Routing Algorithms IJECEIAES
The advent of System-on-Chip (SoCs), has brought about a need to increase the scale of multi-core chip networks. Bus Based communications have proved to be limited in terms of performance and ease of scalability, the solution to both bus – based and Point-to-Point (P2P) communication systems is to use a communication infrastructure called Network-on-Chip (NoC). Performance of NoC depends on various factors such as network topology, routing strategy and switching technique and traffic patterns. In this paper, we have taken the initiative to compile together a comparative analysis of different Network on Chip infrastructures based on the classification of routing algorithm, switching technique, and traffic patterns. The goal is to show how varied combinations of the three factors perform differently based on the size of the mesh network, using NOXIM, an open source SystemC Simulator of mesh-based NoC. The analysis has shown tenable evidence highlighting the novelty of XY routing algorithm.
An Efficient System for Traffic Control in Networks Using Virtual Routing Top...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
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.
DISTRIBUTED TRAFFIC BY LOAD-BALANCING APPROACH FOR AOMDV IN AD-HOC NETWORKScscpconf
Mobile ad hoc network is a collection of wireless mobile nodes, which are connected over a wireless medium. There is no pre-existing communication infrastructure (no access points, no
base stations) and the nodes can freely move and self-organize into a network topology. Such a network can contain two or more nodes. Hence, balancing the load in an Ad hoc network is
important because the nodes have limited communication resources such as bandwidth, buffer space and battery power. This paper presents a new approach to load balancing based on
residual energy of nodes for distribute the traffic evenly among the network nodes. We are exploiting the multipath routing protocol AOMDV, which defines link-disjoint paths between the
source and the destination in every route discovery. We add the energy metric for load balancing (ELB-AOMDV). The performance is compared between ELB-AOMDV and LBAOMDV.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
GPSFR: GPS-Free Routing Protocol for Vehicular Networks with Directional Ante...ijwmn
Efficient and practical communications between large numbers of vehicles are critical in providing high level of safety and convenience to drivers. Crucial real-time information on road hazard, traffic conditions and driver services must be communicated to vehicles rapidly even in adverse environments, such as “urban canyons” and tunnels. We propose a novel routing protocol in vehicular networks that does not require position information (e.g. from GPS) but instead rely on relative position that can be determined dynamically. This GPS-Free Geographic Routing (GPSFR) protocol uses the estimated relative position of vehicles and greedily chooses the best next hop neighbor based on a Balance Advance (BADV) metric which balances between proximity and link stability in order to improve routing performance. In this paper, we focuses primarily on the complexity of routing in highways and solves routing problems that arise when vehicles are near interchanges, curves, and merge or exit lanes of highways. Our simulation results show that by taking relative velocity into account, GPSFR reduces link breakage to only 27% that of GPSR in the dense network. Consequently, GPSFR outperforms GPSR in terms of higher data delivery ratio, lower delay, less sensitivity of the network density and route paths’length
Cooperative load balancing and dynamic channel allocation for cluster based m...ieeeprojectschennai
Cooperative load balancing and dynamic channel allocation for cluster based mobile ad hoc networks
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RIVERBED-BASED NETWORK MODELING FOR MULTI-BEAM CONCURRENT TRANSMISSIONSijwmn
The paper presents a Riverbed simulator implementation with both routing and medium access control (MAC) protocols for mobile ad-hoc network wireless networks with multi-beam smart antennas (MBSAs). As one of the latest promising antenna techniques, MBSAs can achieve concurrent transmissions /
receptions in multiple directions/beams. Thus it can significantly improve the network throughput. However, so far there is still no accurate network simulator that can measure the MBSA-based
routing/MAC protocol performance. In this paper, we describe the simulation models with the implementation of MBSA antenna model in physical layer, MAC layer, and routing layer protocols, all in Riverbed Modeler. We will compare two routing scenarios, i.e., multi-hop diamond routing scenario and multi-path pipe routing. We will analyze the network performance for those two scenarios and illustrate the advantages of using MBSAs in wireless networks.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM) ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel MultiRadios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
A Flexible Software/Hardware Adaptive Network for Embedded Distributed Archit...csijjournal
Embedded platforms are projected to integrate hundreds of cores in the near future, and expanding the interconnection network remains a key challenge. We propose SNet, a new Scalable NETwork paradigm that extends the NoCs area to include a software/hardware dynamic routing mechanism. To design routing pathways among communicating processes, it uses a distributed, adaptive, non-supervised routing method based on the ACO algorithm (Ant Colony Optimization). A small footprint hardware unit called DMC speeds up data transfer (Direct Management of Communications). SNet has the benefit of being extremely versatile, allowing for the creation of a broad range of routing topologies to meet the needs of various applications. We provide the DMC module in this work and assess SNet performance by executing a large number of test cases.
A FLEXIBLE SOFTWARE/HARDWARE ADAPTIVE NETWORK FOR EMBEDDED DISTRIBUTED ARCHIT...csijjournal
Embedded platforms are projected to integrate hundreds of cores in the near future, and expanding the
interconnection network remains a key challenge. We propose SNet, a new Scalable NETwork paradigm
that extends the NoCs area to include a software/hardware dynamic routing mechanism. To design routing
pathways among communicating processes, it uses a distributed, adaptive, non-supervised routing method
based on the ACO algorithm (Ant Colony Optimization). A small footprint hardware unit called DMC
speeds up data transfer (Direct Management of Communications). SNet has the benefit of being extremely
versatile, allowing for the creation of a broad range of routing topologies to meet the needs of various
applications. We provide the DMC module in this work and assess SNet performance by executing a large
number of test cases.
Mobile ad hoc network is a reconfigurable network of mobile nodes connected by multi-hop wireless links and capable of operating without any fixed infrastructure support. In order to facilitate communication within such self-creating, self-organizing and self administrating network, a dynamic routing protocol is needed. The primary goal of such an ad hoc network routing protocol is to discover and establish a correct and efficient route between a pair of nodes so that messages may be delivered in a timely manner. Route construction should be done with a minimum of overhead and bandwidth consumption. This paper examines two routing protocols, both on-demand source routing, for mobile ad hoc networks– the Dynamic Source Routing (DSR), an flat architecture based and the Cluster Based Routing Protocol (CBRP), a cluster architecture based and evaluates both routing protocols in terms of packet delivery fraction, normalized routing load, average end to end delay, throughput by varying number of nodes per sq. km, traffic sources and mobility. Simulation results show that in high
mobility (pause time 0s) scenarios, CBRP outperforms DSR. CBRP scales well with increasing number of nodes.
CROSS LAYER DESIGN APPROACH FOR EFFICIENT DATA DELIVERY BASED ON IEEE 802.11P...pijans
Intelligent Transportation Systems (ITS) have been one of the promising technology that has a great interest attention from many researchers over the world. Vehicular Ad-hoc Network (VANET) communications environment as a part of ITS opens the way for a wide range of applications such as safety applications, mobility and connectivity for both driver and passengers to exploit the transport systems in a smoothly, efficiently and safer way. Several challenging tasks facing adopting VANET functionality for ITS such as modelling of wireless transmission and routing issues. These research issues have become more critical due to the high mobility of vehicles nodes (transmitters and receivers) and unexpected network topology due to the high speed of nodes. In fact, modelling radio propagation channel in VANET environment which considers as one of a stringent communications environment is a challenging task. The selection of a suitable transmission model plays a key role in the routing decisions for VANET. Different propagation models allow calculating the Received Signal Strength (RSS) based on key environmental properties such as the distance between transmitter vehicle and a receiver vehicle, the gain and antenna height of transmitter and a receiver vehicles. Hence, it is useful to calculate RSS and SNR values for a specific propagation model and then these values can be used later for routing decision in order to find the best path with high SNR. This paper evaluates the performance of different transmission models (freespace, two-ray and log-normal) in terms of Receive Signal Strength (RSS). In addition, the performance of such wireless transmission models for vehicular communication in terms of PDR, throughput and delay is evaluated by applying the proposed cross layer routing approach based on IEEE 802.11p. By using MATLAB, the obtained results confirm the best packet delivery ratio for our proposed approach, where it indicates poor quality of DSSS PHY with high number vehicles. The minimum delay achieved when traffic density is decreased.
CROSS LAYER DESIGN APPROACH FOR EFFICIENT DATA DELIVERY BASED ON IEEE 802.11P...pijans
Intelligent Transportation Systems (ITS) have been one of the promising technology that has a great
interest attention from many researchers over the world. Vehicular Ad-hoc Network (VANET)
communications environment as a part of ITS opens the way for a wide range of applications such as safety
applications, mobility and connectivity for both driver and passengers to exploit the transport systems in a
smoothly, efficiently and safer way. Several challenging tasks facing adopting VANET functionality for ITS
such as modelling of wireless transmission and routing issues. These research issues have become more
critical due to the high mobility of vehicles nodes (transmitters and receivers) and unexpected network
topology due to the high speed of nodes. In fact, modelling radio propagation channel in VANET
environment which considers as one of a stringent communications environment is a challenging task. The
selection of a suitable transmission model plays a key role in the routing decisions for VANET. Different
propagation models allow calculating the Received Signal Strength (RSS) based on key environmental
properties such as the distance between transmitter vehicle and a receiver vehicle, the gain and antenna
height of transmitter and a receiver vehicles. Hence, it is useful to calculate RSS and SNR values for a
specific propagation model and then these values can be used later for routing decision in order to find the
best path with high SNR. This paper evaluates the performance of different transmission models (free-
space, two-ray and log-normal) in terms of Receive Signal Strength (RSS). In addition, the performance of
such wireless transmission models for vehicular communication in terms of PDR, throughput and delay is
evaluated by applying the proposed cross layer routing approach based on IEEE 802.11p. By using
MATLAB, the obtained results confirm the best packet delivery ratio for our proposed approach, where it
indicates poor quality of DSSS PHY with high number vehicles. The minimum delay achieved when traffic
density is decreased
Energy efficiency cross layer protocol for wireless mesh networkIJCNCJournal
Wireless mesh network (WMN) is a novel emerging tec
hnology that will change the world more effectively
and efficiently. It is regarded as a highly promisi
ng technology being increasingly important in mobil
e
wireless networks of the future generation. In this
paper, we consider energy management for wireless
mesh networks from a point of view that started rec
ently to attract the attention means the conservati
on of
energy for operational and the environment reasons
which is known as the Green Networking. This paper
discusses different routing protocols to establish
a protocol which considers energy efficiency. The e
xisting
protocols are compared using the basic functions of
routing and the suggest protocol is designed to
overcome some of their shortcomings. We are focusin
g on the conception of the cross-layer routing
protocol that is implemented in TDMA (Time Division
Multiple Access) wireless mesh networks based
MAC protocol.
Performance evaluation of MANET routing protocols based on QoS and energy p...IJECEIAES
Routing selection and supporting Quality of Service (QoS) are fundamental problems in Mobile Ad Hoc Network (MANET). Many different protocols have been proposed in the literature and some performance simulations are made to address this challenging task. This paper discusses the performance evaluation and comparison of two typical routing protocols; Ad Hoc On-Demand Distance Vector (AODV) and Destination-Sequenced DistanceVector (DSDV) based on measuring the power consumption in network with varing of the QoS parameters. In this paper, we have studied and analyzed the impact of variations in QoS parameter combined with the choice of routing protocol, on network performance. The network performance is measured in terms of average throughput, packet delivery ratio (PDR), average jitter and energy consumption. The simulations are carried out in NS-3. The simulation results show that DSDV and AODV routing protocols are less energy efficient. The main aim of this paper is to highlight the directions for the future design of routing protocol which would be better than the existing ones in terms of energy utilization and delivery ratio.
Modified q aware scheduling algorithm for improved fairness in 802.16 j networksIJCNCJournal
Deployment of Multi-hop Relays in WiMax based Cellu
lar Networks is considered as a cost effective
solution to increase the Coverage area of Base Stat
ion and also to improve the Network Capacity with h
igh
quality short links. Scheduling became a challengin
g task in these Multi-hop Relay Wireless Cellular
Networks of IEEE 802.16j standard. H. Chen, X. Xie
and H. Wu proposed a Q-aware Scheduling
Algorithm in which back-pressure flow control mecha
nism is used to reflect current Q size of the Relay
s
and considered high back-pressure links to include
in Concurrent Transmission Scenarios, to maximize t
he
throughput. This focus on high back-pressure links,
leads to starvation of Mobile Stations having low
back-
pressure links, resulting unfairness in some cases.
To remedy this situation, a Fair Link Inclusion (F
LI)
mechanism is applied in Greedy Algorithm of Q-aware
Scheduling Algorithm. Simulation results show that
Modified Q-aware Scheduling Algorithm with FLI mech
anism has reasonable improvement in fairness and
maintaining steady throughput when compared with ex
isting algorithms.
Simulation based comparison of routing protocols in wireless multihop ad hoc ...IJECEIAES
Routing protocols are responsible for providing reliable communication between the source and destination nodes. The performance of these protocols in the ad hoc network family is influenced by several factors such as mobility model, traffic load, transmission range, and the number of mobile nodes which represents a great issue. Several simulation studies have explored routing protocol with performance parameters, but few relate to various protocols concerning routing and quality of service (QoS) metrics. This paper presents a simulation-based comparison of proactive, reactive, and multipath routing protocols in mobile adhoc networks (MANETs). Specifically, the performance of AODV, DSDV, and AOMDV protocols are evaluated and analyzed in the presence of varying the number of mobile nodes, pause time, and traffic connection numbers. Moreover, Routing and QoS performance metrics such as normalized routing load, routing packet, packet delivery ratio, packet drop, end-to-end delay, and throughput are measured to conduct a performance comparison between three routing protocols. Simulation results indicate that AODV outperforms the DSDV and AOMDV protocols in most of the metrics. AOMDV is better than DSDV in terms of end-to-end delay. DSDV provides lower throughput performance results. Network topology parameters have a slight impact on AODV performance.
Performance Comparison and Analysis of Mobile Ad Hoc Routing ProtocolsCSEIJJournal
A mobile ad hoc network (MANET) is a wireless network that uses multi-hop peer-to-peer routing instead
of static network infrastructure to provide network connectivity. MANETs have applications in rapidly
deployed and dynamic military and civilian systems. The network topology in a MANET usually changes
with time. Therefore, there are new challenges for routing protocols in MANETs since traditional routing
protocols may not be suitable for MANETs. Researchers are designing new MANET routing protocols
and comparing and improving existing MANET routing protocols before any routing protocols are
standardized using simulations. However, the simulation results from different research groups are not
consistent with each other. This is because of a lack of consistency in MANET routing protocol models
and application environments, including networking and user traffic profiles. Therefore, the simulation
scenarios are not equitable for all protocols and conclusions cannot be generalized. Furthermore, it is
difficult for one to choose a proper routing protocol for a given MANET application. According to the
aforementioned issues, this paper focuses on MANET routing protocols. Specifically, my contribution
includes the characterization of different routing protocols and compare and analyze the performance of
different routing protocols.
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RIVERBED-BASED NETWORK MODELING FOR MULTI-BEAM CONCURRENT TRANSMISSIONS
1. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 9, No. 6, December 2017
DOI: 10.5121/ijwmn.2017.9601 1
RIVERBED-BASED NETWORK MODELING FOR
MULTI-BEAM CONCURRENT TRANSMISSIONS
Ji Qi1, Xin Li1, Shivam Garg2, Fei Hu1, Sunil Kumar2
1
Department of Electrical and Computer Engineering, University of Alabama,
Tuscaloosa, AL
2
Department of Electrical and Computer Engineering, San Diego State University, San
Diego, CA
ABSTRACT
The paper presents a Riverbed simulator implementation with both routing and medium access control
(MAC) protocols for mobile ad-hoc network wireless networks with multi-beam smart antennas (MBSAs).
As one of the latest promising antenna techniques, MBSAs can achieve concurrent transmissions /
receptions in multiple directions/beams. Thus it can significantly improve the network throughput.
However, so far there is still no accurate network simulator that can measure the MBSA-based
routing/MAC protocol performance. In this paper, we describe the simulation models with the
implementation of MBSA antenna model in physical layer, MAC layer, and routing layer protocols, all in
Riverbed Modeler. We will compare two routing scenarios, i.e., multi-hop diamond routing scenario and
multi-path pipe routing. We will analyze the network performance for those two scenarios and illustrate the
advantages of using MBSAs in wireless networks.
INDEX TERMS
Multi-beam Smart Antennas (MBSAs), Medium Access Control (MAC), Multi-path routing, Riverbed
Modeler.
I. INTRODUCTION
Today the most popular antenna used in wireless devices is the omni directional antenna.
However, such an antenna radiates energy in all the 360-degree spaces, which results in poor
spatial reuse and strong interference among the neighboring nodes. A promising new type of
antenna, called multi-beam smart antenna (MBSA), can concurrently send data to different
angles/beams and sperate the signal domains between the beams. Thus a MBSA could
significantly improve the spatial reuse and the network throughput. By using MBSAs, a node can
achieve concurrent packet reception (CPR) and concurrent packet transmission (CPT). This
means that ideally the node throughput can be enlarged for N times if there are N beams in the
MBSA, compared to general directional antenna with only one beam.
A mobile ad-hoc network (MANET) [1] consists of mobile nodes which communicate with each
other either directly or relying on relay nodes, but without the use of fixed infrastructure or
centralized administration. The nodes have to execute all network functions such as discovering
the network topology or delivering packets via routing protocols. In MANETs every node is a
potential router. Therefore, routing scheme plays an important role for data forwarding in
MANETs where each mobile node can act as a relay in addition to being a source or destination
2. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 9, No. 6, December 2017
2
node [2], [3]. Many routing protocols have been proposed to provide data forwarding services for
MANETs. They can be classified as reactive (on-demand) or proactive (the routing path is always
ready for use). A popular reactive protocol is Ad-Hoc on Demand Distance Vector Routing
Protocol (AODV) [4], and a popularly used proactive scheme is Optimized Link State Routing
Protocol (OLSR) [5]. Some existed routing protocols are enumerated in Fig. 1.
Fig. 1. MANET routing protocols
However, very little research has been conducted on MBSAoriented routing or MAC design for
MANETs. MBSAs can bring many benefits to MANET (such as improving data throughput and
shorten routing delay). But the routing/MAC design for MBSA-based networks also raises some
challenging issues. Here we list a few:
1) If using MBSAs, it is prohibitive to make some of the beams operate in transmission (Tx)
mode while others in reception (Rx) mode. In other words, a node should work either as a
transmitter (with all beams in Tx mode) or a receiver (all in Rx mode). It can not send AND
receive packets at the same time. This is mainly because that its antenna design requires that all
beams’ coefficient vectors be determined in the same control matrix. If Tx and Rx modes are
mixed at the same time, the side lobe of those beams working in Tx mode would seriously
interfere with those beams working in Rx mode due to the energy leakage issues.
2) In order to make full use of the benefit of the concurrent transmissions, all neighboring nodes
(especially the nodes within two hops of range) need to be carefully coordinated. Clock/schedule
synchronization turns out to be a serious issue in MBSA-based networks since it cannot just rely
on the use of request-to-send (RTS)/ clear-to-send (CTS) and acknowledge (ACK) messages.
3) Despite the fact that theoretically a MBSA is able to enlarge the node capacity by N times
(where N is the number of beams of the antenna), a specific MAC protocol is needed to control
the beam schedule as well as the beam-based distributed coordination function (DCF). Most of
the conventional MAC protocols are designed for omnidirectional or single-directional nodes, and
use traditional IEEE 802.11 protocols. However, to take advantage of the high capability of
multi-beam transmissions, a new MAC scheme is needed.
Riverbed Modeler (formerly called OPNET) [6] is a popular network simulation software
package. It provides a flexible and accurate simulation platform for evaluating the performance of
verious networking protocols. Riverbed Modeler provides the access to a rich set of API calls.
The process models of the network nodes are implemented in the programming language called
3. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 9, No. 6, December 2017
3
Proto-C, and are constructed by using finite state machine (FSM)-based transition diagrams. The
features of Riverbed software allow the test of standardized protocols (such as TCP/IP), as well as
the development of new communication protocols and networking paradigms. We have used
Riverbed Modeler version 18.5 to implement multi-path data transmission schemes with MBSAs
and comprehensively analyzed its routing performance.
This paper takes the first step to build the Riverbed-based MBSA-oriented network simulator.
Riverbed is a commercialized network simulation tool, and can more accurately reflect the actual
network performance than other network simulation tools such as ns-3. We will first introduce the
background knowledge of MBSA and Riverbed Modeler, and then summarizes some related
works in Section II. In section III, we will discuss our design of MBSA model and its MAC layer
protocol in Riverbed. In section IV, we provide a detailed description of modeling two multi-path
routing scenarios, followed by the conclusions in Section V.
II. BACKGROUND AND RELATED WORKS
There has been much research work conducted on MANET performance analysis by using
Riverbed (OPNET) Modeler. Agustin Zaballos et al. [7] provided a comparative study about four
routing protocols, i.e., DSR, TORA, AODV and OLSR, for MANETs. Naveen Bilandi and Harsh
K Verma [8] conducted the similar study, and measured the performance of different routing
protocols by using three metrics: delay, network load, and throughput. Sheela Ganesh Thorenoor
[9] presented the implementation process and compared the protocols that are based on distance
vector or link state algorithms.
Vasil Hnatyshin and Hristo Asenov [10] introduced the design and implementation of GeoAODV
routing protocol in OPNET Modeler, which used Global Positioning System (GPS) coordinates to
search the area where a path to the destination is likely to be located. Rani Al-Maharmah et al.
[11] provided an overview of OPNET Modeler architecture and described a practical
methodology to add new MANET routing protocols to OPNET Modeler by using the Multi-
Aware Cluster Head Maintenance (MACHM). Regarding antenna design, John A. Stine [12]
described the details of how to build models of adaptive antennas in OPNET by using the radio
process model and radio pipeline stages.
However, none of the above studies involves the MBSAbased protocol test, which requires
special concurrent communication protocols in different layers. For example, in physical layer, a
new antenna model needs to be built and added to the Riverbed library. The MAC layer needs to
call such an antenna model to implement the synchronized collision avoidance control, and the
routing layer should use some sort of multipath routing with multi-beam coordinations to fully
utilize the features (CPT/CPR) of MBSAs. In the following discussions we will provide our
Riverbed implementation details for the above aspects.
III. NETWORK SIMULATION ARCHITECTURE IN RIVERBED MODELER
In Riverbed Modeler, the network architecture is modeled as a layered structure. The process
domain is in the lowest layer, which contains the actual functions of the modeled protocols. The
process models consist of state transition diagrams as well as some blocks of C codes. Each
process is designed to respond to different events/interrupts. We can dynamically create child
processes for each process.
4. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 9, No. 6, December 2017
4
The node domain is responsible for creating the models of individual devices and relies on the
process models to simulate the behaviors of different function modules. There are some basic
building blocks including processors, queues, and transceivers. Processors are fully
programmable via their process model. The Queue modules can buffer and manage data packets,
and the transceivers are the interfaces of the node.
The top layer, i.e., network domain, represents a complete system of interconnected devices.
Besides nodes, network models also have links and subnets. Either point-to-point or bus links can
be used in the networks.
In Riverbed Modeler, packets are the information-carrying entities that circulate among system
components. We can dynamically create and destroy the packets during the simulations. Packets
can either be unformatted or formatted. Unformatted packets have no user-defined data fields
while formatted packets have one or more fields. A single system may rely on multiple types of
packets with different formats.
The simulations in Riverbed Modeler are event-driven. In this programming paradigm, events are
specific activities that occur at a certain time, and the simulation time advances when an event
occurs. Event-driven method is naturally suited to the applications whose control flow are based
on the internal or external events. But the accuracy of results is limited by the sampling
resolution.
Riverbed Modeler allows a realistic estimation of the performance and behavior for the executed
simulations. It has several mechanisms to collect the data. The output data is generated after each
simulation. Desired statistics are explicitly recorded in the appropriate output files. The
programmer can specify a list of probes, each of which indicates that a particular statistic should
be collected in this run. Advanced forms of probes can be defined by the users through its probe
editor.
IV. MBSA MODEL AND MAC LAYER DESIGN
A. Multi-beam Antenna
Figure 2 illustrates the typical single-beam antenna as well as MBSA models. As shown in Fig.
2(a), a single beam has one main lobe and several side lobes. The side lobes cover only small
areas, and are thus not capable of establishing effective communications. The main lobe covers a
much larger area with a long propagation distance. In Fig. 2(b), however, we could see multiple
main lobes (marked by blue color) face different directions. A node can dispatch different packets
in multiple beams concurrently. Compared with MIMO antennas, MBSAs have much lower
manufacturing cost and control complexity.
(a) single-beam
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(b) multi-beam antennas
Fig. 2. An illustration of (a) single-beam, and (b) multi-beam antennas.
In Riverbed Modeler, we use the Antenna Pattern Editor to create, modify, and view antenna
pattern models. These models specify antenna gain in three-dimensional space. They also contain
orientation information that is used to make the antenna point to a specific target.
An antenna pattern model represents the three-dimensional gain of an antenna by specifying the
gain at regular intervals of the 3D pattern. To determine these intervals, the pattern is
decomposed into a set of horizontal slices called polar planes. Fig. 3 shows the polar plot of our
designed antenna, and Fig. 4 gives a 3D view of the antenna. Within each polar plane, the
antenna’s gain is specified at regular angular intervals (azimuth values).
Fig. 3. Antenna pattern polar plot
Fig. 4. Antenna pattern 3D view
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B. MAC with Multi-Beam Smart Antennas
There is little research on MAC design for MBSA-based networks. Vivek Jain’s work [13]
provides us some valuable inspirations. He designed an across-layer hybrid MAC (HMAC) that
might support concurrent communications in multiple outgoing links, and proposed a WMN
architecture with heterogeneous antenna technologies.
As mentioned before, one of the principal concerns in multi-beam MAC design is to leverage its
CPT/CPR features. Both CPR and CPT constraints require the synchronization of the transmitting
nodes, i.e., starting their transmissions for the common receivers at the same time and also
initiating transmissions in different beams of the transmitter’s antenna at the same time.
Riverbed Modeler adopts 802.11 [14] by default as MAC layer specification. If we take a closer
look at each node model, we can find that 802.11 protocol is defined in a process model called
wlan mac. All the MAC-related functions are defined in this process, and the most important
functions are listed as follows.
1) wlan higher layer data arrival: this function starts the processing of the higher layer packets,
queues it if (1) the packet is accepted and (2) there is still sufficient space in the higher layer data
buffer.
2) wlan frame transmit: this function prepares and transmits the appropriate frames.
3) wlan prepare frame to send: this function sets appropriate fields in the packet format for Data,
Cts, Rts or Ack.
4) wlan interrupts process: this function handles interrupts such as stream interrupt (from lower
and higher layers).
5) wlan physical layer data arrival: this function processes the frame received from the lower
layer, decapsulates the frame and sets appropriate flags if the station needs to generate a response.
6) wlan data process: this function handles defragmentation process and also send data to the
higher layer.
Fig. 5 gives a compact view of 802.11 MAC in Riverbed Modeler and also shows the processing
order of these functions.
In our simulations, we define the node that is located in the intersections of two or more routes as
a bottleneck node. There is no bottleneck node in 802.11 protocols as none of
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Fig. 5. 802.11 MAC in Riverbed Modeler
The devices in 802.11 has the capability of performing CPT or CPR. We implement local
synchronization scheme in each bottleneck node by using a four-way handshake scheme.
We create a new function named ’wlan physical layer multiple data arrival’ for each bottleneck
node to handle the CPT and CPR cases. This function analyzes each RTS/CTS received by
different beams. Based on the antenna information from the incoming packets, the bottleneck
node can select the corresponding beam to respond to the incoming data. Our model counts the
number of CTS/RTS messages exchanged at certain time and checks if four beams are
sending/receiving the same type of packets.
For each bottleneck node with multiple antenna beams, we can either share the same queue for all
beams, or use different data queues for different beams. However, a packet at the head of a queue
may block other packets behind it for indefinite time if its intended outgoing beam is busy. Thus,
to overcome the Head of Line (HOL) blocking issue [15], we maintain a separate data queue for
each beam of the bottleneck node, which is shown in Fig. 6.
A neighbor-information table called Hybrid Network Allocation Vector (HNAV) is also
maintained in our MAC layer implementation. The information in HNAV table includes the
following 3 aspects:
1) the beam the neighbor falls within, which is represented by DoA information [16].
2) how long the neighbor is engaged in the communications.
3) whether or not this neighbor should maintain silence in the current beam.
Our model checks the HNAV table during data transmissions and updates the HNAV information
when it receives channel control packets.
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Fig. 6. Bottleneck node model with multiple data queues
V. MULTI-PATH DATA TRANSMISSION NETWORK IMPLEMENTATION
A. Implementation of Routing Protocols in Riverbed Modeler
Process model ip dispatch exists in every layer-3 node in Riverbed Modeler. Almost all the
MANET routing protocols are identified and invoked in this process. Some important
modifications must be made in routing layer for the nodes with MBSAs.
Using AODV protocol as an example. In Riverbed Modeler, AODV is defined as a process model
called aodv rte, which is a child process of ip dispatch. The software uses Finite State Machine
(FSM) [17] to simulate the behavior of each process. As shown in Fig. 7, the process model
consists of two states: init and wait. The init state is responsible for the initialization of various
data structures including state variables, local statistics, buffers, and protocol parameters. This
state is a forced state, which is shown as a green button. A forced state does not allow a pause
during the process. In a force state, the process can perform the following actions: (1) invoke the
enter executives; (2) invoke the exit executives; (3) evaluates all condition statements, and (4) if
exactly one condition statement is evaluated to be true, the transition is traversed to the next state.
Therefore, once the initialization is complete, the process model moves into the wait state which
models the operation of the AODV protocol. However, this is an unforced state (red button),
which allows a pause during the process. In the unforced state, the process will (1) invoke the
enter executives; (2) places a marker in the middle of the state; (3) release control to the
simulation Kernel and become idle; and (4) resume at the marker and process the exit code when
it is invoked next. The aodv rte process is in idle state until an event that is packet arrival or an
expiry timer occurs. Based on the event type, the process performs the necessary actions by
calling one or multiple functions.
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Fig. 7. Riverbed aodv rte process model
Process aodv rte uses one data structure named ’aodv request table’ to do the route discovery, and
uses another data structure ’aodv route table’ to update and store the route information. The main
function gets access to these two tables by creating ’aodv request entry’ and ’aodv route entry’,
respectively. Thus these two data structures and the related functions which use the data
structures, are the key parts of the routing layer that need to be updated according to the MAC
layer state.
The contents in aodv request entry include:
• target _address
• request_ id
• current_ ttl_ value
• insert_ time
• current _request_ expiry _time
• rreq _retry
From the routing discovery perspective, each node in the network discovers a new route by
sending a hello packet to the neighboring node. The node with a MBSA should have a similar
discovery strategy as the node with an omnidirectional antenna. The only difference is that we
should indicate by which beam the hello package is sent if we use a MBSA. Thus we need to add
an index named ’beam id’ into the ’aodv request table’ data structure.
The contents in aodv route entry include:
• destination_ prefix
• destination_ sequence_ number
• route _entry_ state
• next _hop _address
• next_ hop_ port_ information
• hop _count
• route _expiry _time
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Similarly, we need to add an index named ’beam _id’ into the ’aodv_ route_ table’ data structure.
Both table data structures are defined in the header file ’aodv.h’. Here ’aodv _request _entry’ is
further divided into two data structures, i.e., AodvT _Orig_ Request _Entry’ and ’AodvT_
Forward _Request_ Entry’.
We also need to change the packet format of ’RREQ’ and ’RREP’, and put ’beam id’ information
in each packet. All the packet formats are defined in the header file ’aodv_ pkt _support.h’ while
all the packet creation functions are defined in the file ’aodv _pkt_ support.ex.c’. To change the
format of ’RREQ’ and ’RREP’ messages, we need to modify the corresponding functions ’aodv
_pkt _support _rreq _option _create’ and ’aodv _pkt_ support_ rrep _option _create’.
The file ’aodv _request_ table.ex.c’ contains all the operation functions of the request table.
When we send a new route request, we need to add it into the request table. We also need to
change the related functions ’aodv _request_ table_ orig_ rreq_ insert’ and ’aodv_ request _table
_forward _rreq _insert’.
For the control functions of the routing table, we only need to change the function ’aodv _route_
table_ entry _create’ function which is defined in ”aodv_ route_ table.ex.c’.
Figure 8 shows the flowchart of AODV routing in Riverbed Modeler. Some important functions
in the process model are listed in Italic style.
Fig. 8. AODV routing flowchart in Riverbed Modeler
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We can always obtain the beam status information (such as orientation) from MAC and physical
layers. If a node has occupied the channel and known its destination node in the MAC layer, we
can easily determine which beam is used to send the data. Thus we can pass these parameters
from lower layers to higher layers through the node model.
Based on the definition of the OSI 7-layers network model [18], routing layer is located in the
network layer, which is further divided into 2 parts: the lower layer is routing layer and the upper
layer is IP layer. In Riverbed Modeler, each node (either a transmitter or a receiver) should create
a network interface before communicating with each other. And each interface needs to be
assigned with an IP address. From Fig. 6 we can see that in MAC layer we have attached four
pairs of ’radio _txrx’ models to one node. Riverbed assigns an IP address to each interface by
default. Thus here we have four different addresses for one node, which is disallowed in a typical
network. To solve the ’IP addressing’ problem, we combine all the four pairs of radio interfaces
as an entire entity. They are assigned to the same IP address and are always treated equally. All
the modifications of IP assignment functions are located in the file ’ip_ auto_ addr_ sup v4.ex.c’.
B. Multi-hop Diamond Routing Scenario
We have also designed a multi-hop diamond routing scheme in Riverbed. Fig. 9 shows the
network topology in Riverbed Modeler. In this scenario, we have used 4 bottleneck nodes and 12
regular nodes to realize a 6-hop multi-path data transmission architecture, which is called
’diamond routing’.
Fig. 9. Multi-hop diamond routing scenario
Fig. 10 shows more details about this scenario. From the figure we can see that the nodes
1,6,11,16 are bottleneck nodes and the others are regular nodes. Each bottleneck node is equipped
with eight beams (half for CPT and the other half for CPR), while the regular nodes are equipped
with two beams (one for transmission and the other for reception). In this scenario, node 1 is the
source node and node 16 is the final destination node, and the rest of the nodes in the network
play the roles of data relaying. The detailed data transmission processes are as follows:
1) Node 1 generates the data streams and splits them into four data queues.
2) The four beams (in transmission mode) in node 1 send hello package and RREQ
simultaneously to the corresponding receiving beams of nodes 2,3,4,5 to build a new route.
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3) The nodes 2,3,4,5 exchange RTS and CTS with node 1 simultaneously to start data
transmissions.
4) Node 1 sends its data through 4 beams to nodes 2,3,4,5 simultaneously.
5) Nodes 2,3,4,5 receive the data, decode the data packet head, and analyze the final destination.
6) The other beams of nodes 2,3,4,5 will send hello package and RREQ again simultaneously to
the corresponding receiving beams of node 6 to build a new route.
7) Node 6 exchanges RTS and CTS with nodes 2,3,4,5 simultaneously to start another hop of data
transmission.
8) Nodes 2,3,4,5 send its data to node 6 simultaneously.
9) Node 6 receives the data, decodes the data packet head and analyzes the final destination.
10) Node 6 will again, build a new route and forward the received data to nodes 7,8,9,10
simultaneously, until all the data reached node 16.
The bottleneck nodes 6 and 11, which serve as the relay nodes in this scenario, require packet
distribution and beam switching schedule. Local synchronization is also required here, since all
the eight beams of the node will be used during the data transmissions.
To make things more clear, we set a packet relay scheme in each bottleneck relay node. Taking
node 6 as an example, from Fig. 10 we can obtain the position and index of each antenna beam.
Each packet from node 2, which is received by beam 1, will be pushed into the outgoing queue of
beam 5. Then the packets will be sent to node 7. Similarly, the packets received by beam 2 will
go to beam 6, etc. This process helps us better balance the traffic loads in different links.
Our packet relay scheme is mainly implemented in process wlan _mac. For each received packet,
the relay node will first perform the address resolution. After that the packet will be pushed back
to the MAC layer. As mentioned in Section IV, the function ’wlan_ data_ process’ will handle the
packets which need to be forwarded to the next hop. We have rebuilt the function ’wlan _data_
process’. In this new function, we first get the ’beam_ id” of each incoming packet and then push
it into the corresponding queue by using the function ’wlan _hlpk_ enqueue’.We then add a
’queue_ id’ to the original ’wlan _hlpk _enqueue’ function, which indicates the index of different
queues.
Moreover, we need to carefully setup the time schedules because CPT and CPR cannot occur
simultaneously, i.e., they should occur alternatively in the same node. For example, node 6 will
first receive four data packets from nodes 2,3,4,5. Although it is a concurrent transmission, some
time deviations may still occur. Considering the different queueing delays and data amounts in
each beam, we need to make the ’fastest’ beam wait for the ’slowest’ beam. Thus here we split
the timeline into several small time slots. In each slot only half of the beams work, either in CPT
or CPR mode.
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C. Multi-path Pipe Routing Scenario
To further improve the network throughput, we propose a multi-path pipe routing scenario. Fig.
11 shows the network distribution structure in Riverbed Modeler. In this scenario, every node is
set to be a bottleneck node as multiple data exchanges can happen between each pair of nodes.
We have finished a 2x2 ’pipe’ routing scenario. A more complicated network scenario can be
easily setup based on such a pipe architecture.
The detailed information of this scenario is shown in Fig. 12. In this scenario, node 1 is the source
node and node 6 is the destination node. Nodes 2,3,4,5 are relay nodes, and each node has three
antenna beams. There are some data links
Fig. 10. Multi-hop diamond routing scenario: packets distribution and beam switching schedule
Fig. 11. Multi-path pipe routing scenario
between those four nodes, which are separated by different pairs of antenna beams. The following
process shows how the system operates in multiple steps:
Fig. 12. Multi-path pipe routing scenario: packets distribution and beam switch schedule
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1) Node 1 generates the data streams and splits them into two data queues. Then Node 1 sends
hello package and RREQ simultaneously to the corresponding receiving beams of nodes 2,3 to
build a new route. Then nodes 2,3 exchange RTS and CTS with node 1 to start data
transmissions.
2) Node 1 sends its data through 4 beams to nodes 2,3 simultaneously. After receiving the data,
nodes 2,3 decode the data packets head and analyze the final destination.
3) Nodes 2,3 will send hello package and RREQ simultaneously to build two routes with nodes
4,5, respectively. Then nodes 4,5 will exchange RTS and CTS with nodes 2,3 to start in-pipe data
transmission.
4) After receiving data from nodes 2,3, nodes 4,5 will build a new route to node 6 and forward
their data to the final destination.
The data links among the nodes 2,3,4,5 are the key part of this scenario. After receiving data
packets from the source node, the first-level relay nodes 2 and 3 will further divide the incoming
data streams into two data queues. Then each half of the data packets will be sent to nodes 4 and
5 through antenna beams which point to different directions. While for the second-level relay
nodes 4 and 5, after receiving data from nodes 2 and 3, they need to mix the two incoming data
streams together and push them into the outgoing data queue. The implementation of data streams
split / combination is also made in the function ’wlan _data_ process’ of the process ’wlan_ mac’.
Since there is an intersection node in the middle of the data links, a more accurate time schedule
is implemented to avoid signal interference. We first set nodes 2 and 3 in reception (Rx) mode,
keep them receiving data packets for certain duration to get enough packets to split. Then we
change it to transmission (Tx) mode and retransmit their data to the next relay node
simultaneously. After a time slot we change them back to Rx mode. Nodes 4 and 5 will also
change their working modes alternately, according to the routing packets received from nodes 2
and 3.
VI. RESULT ANALYSIS AND DISCUSSIONS
We have performed Riverbed simulations to verify the benefits of our proposed MAC and routing
schemes. Table I shows the used MAC settings. We have changed some default parameters in
each ’node model’ for all the tested scenarios to better enhance the routing performance.
For traffic generation parameters, we set the inter-arrival time of each packet to 0.004s and the
size of packet to 512 bytes. The data stream generation will start from the 10th second and end in
the 30th second during the simulations.
We first design a simple CPT-CPR scenario to evaluate the performance of our MAC with
MBSAs. From Fig. 13 we can see that there are ten nodes in this scenario. Nodes 1 and 6 are
bottleneck nodes while the others are regular nodes. On the left part of the scenario, nodes
7,8,9,10 are sending packets simultaneously to node 1. This is a CPT case. On the right side of
the scenario, nodes 2,3,4,5 are receiving packets simultaneously from node 6. This is a CPR case.
Node 6 will use four different data queues to generate packets at the same time.
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Table I Mac Settings In Our Riverbed Simulation
Fig. 13. CPT-CPR scenario
Fig. 14 shows the throughput of node 1. The throughput of node 6 is almost the same as node 1
since we use the same schedule in our CPT-CPR scenario. Based on the packet generation
settings we can see that each regular node sends 250 packets every second. From the figure we
can see that MBSA can significantly increase the throughput of the bottleneck nodes. Fig. 15
shows the average packet delay of node 1 in CPT-CPR scenario (the result of node 6 is also quite
similar).
For multi-hop diamond routing scenario, we compare it with a normal multi-hop routing scenario,
which is shown in Fig. 16. In normal multi-hop routing scenario, node 1 is the source node and
node 7 is the destination node. All the data packets will be forwarded through the same route.
Both multi-hop diamond routing and its control group have six hops in total. Table II shows the
selected routing settings for the normal multi-hop routing scenario.
Fig. 17 shows the network throughput for multi-hop diamond routing scenario as well as the
normal multi-hop forwarding scenario. Compared with normal multi-hop scenario, our diamond
routing scheme can achieve satisfactory through
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Fig. 14. Throughput of node 1 in CPT-CPR scenario
Fig. 15. Packet Delay of node 1 in CPT-CPR scenario
put in the first two hops, but its throughput goes down as the number of the hops increases, which
is reasonable in multihop data relay case. Although the diamond routing scenario has three more
data links in every hop, local synchronization in bottleneck node needs certain communication
overhead. More hops in data transmission means longer time to synchronize the CPR and CPT
operations.
Fig. 18 shows the average packet delay for multi-hop diamond routing scenario and normal multi-
hop scenario. From the figure we can see that the delay of our proposed scenario is a little higher
than the compared one. There are three reasons for this. First, local synchronization is a time-
consuming process. Second, our routing layer has multi-neighbor address analysis and multi-
queue packet distribution tasks to perform, which also takes some time. Third, we need to put
more information (beam-id) into channel control packets. However, with the increase of hops, the
difference between those two scenarios becomes negligible.
For multi-path pipe routing scenario, we compare it with a normal multi-path routing scenario,
which is shown in Fig. 19. In normal multi-path routing scenario, we also have 6 nodes,
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Fig. 16. Normal multi-hop routing scenario
Table Ii Routing Settings In Normal Multi-Hop Routing Scenario
but all the nodes in the network are disjoint ones, i.e., without coupled multi-beam forwarding.
After receiving packets from node 1, node 2 will only send data to node 4 while node 3 will
forward all its data to node 5. There is no intersection node in the middle of any two data paths.
Figure. 20 shows the simulation results for multi-path pipe routing scenario and normal multi-
path scenarios. We can see that our ’pipe’ routing architecture can further enhance the network
throughput compared with general multi-pathscenario. Signal interference is still a key factor and
has a great impact on the result.
Fig. 21 shows the average packet delay for multi-path pipe routing and normal multi-path routing
scenarios. Because a strict time schedule is implemented within each bottleneck node, we get a
higher packet delay in our pipe scenario. However, compared with the large improvement of
network throughput, the slight sacrifice of packet delay can be tolerated.
VII. CONCLUSIONS
In this paper we have presented the Riverbed-based design and implementation of multi-path data
transmission schemes in the MANET with MBSAs. Specifically, we have described the
architecture of the simulator for modeling MANET routing protocols, and provided a detailed
procedure of implementing the corresponding MAC and routing layers for network nodes with
MBSAs, by using Riverbed Modeler version 18.5. Our simulation results showed that with the
help of multi-beam antennas, the throughput of the whole network could be improved. Currently
we are investigating the new CPT/CPRforwarding schemes for improving the performance of our
above framework. This paper could shed some light for other researchers who may use Riverbed
tools to study and evaluate the performance of wireless networks.
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Fig. 17. Network throughput comparison between multi-hop diamond routing and normal multi-hop routing
Fig. 18. Packet delay comparison between multi-hop diamond routing and normal multi-hop routing
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Fig. 19. Normal multi-path routing scenario
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Fig. 20. Network throughput comparison between multi-path pipe routing and normal multi-path routing
Fig. 21. Packet delay comparison between multi-path pipe routing and normal multi-path routing