Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over Maciocco et al. (Patent No: US20220329522A1), hereinafter, Maciocco, in view of Herb et al. (Patent No: US20230017632A1), hereinafter, Herb.
Regarding Claim 1, Maciocco teaches,
A device, comprising: a processor; at least one network interface controller configured to provide access to a network; and a memory communicatively coupled to the processor, wherein the memory comprises a network path optimization logic that is configured to: -Fig. 9 (904, 906, 920), Paragraph [0154] ([0154] recites, “…In some examples, the NIC 920 may be embodied as part of a system-on-a-chip (SoC) that includes one or more processors or included on a multichip package that also contains one or more processors. In some examples, the NIC 920 may include a local processor (not shown) and/or a local memory (not shown) that are both local to the NIC 920. In such examples, the local processor of the NIC 920 may be capable of performing one or more of the functions of the compute circuitry 902 described herein. Additionally, or alternatively, in such examples, the local memory of the NIC 920 may be integrated into one or more components of the client compute node at the board level, socket level, chip level, and/or other levels.”)
identify network path options between two devices within the network, -Fig. 9, Paragraph [0067] ([0067] recites,” A multi-layer Discovery and Context Monitoring Protocol (DCMP) may be utilized to maintain information about status, availability, quality, and probability of failure, degradation, or congestion, etc., of links or paths in the network(s). The DCMP may allow for immediate or prioritized selection of alternate or redundant links or paths when a fault or other similar issue is detected. This may aid in reducing or minimizing latency when switching to the alternate link or path.” )
wherein the network comprises a plurality of transport subsystems; -Fig. 9, Paragraph [0022][0143]([0022] recites, “Network protocol transport level optimizations provided between communicating nodes to minimize packet losses, provide user-defined level of reliability and improve latency performance.” [0143] recites, “In the simplified example depicted in FIG. 9, an Edge compute node 900 includes a compute engine (also referred to herein as “compute circuitry”) 902, an input/output (I/O) subsystem (also referred to herein as “I/O circuitry”) 908, data storage (also referred to herein as “data storage circuitry”) 910, a communication circuitry subsystem 912, and, optionally, one or more peripheral devices (also referred to herein as “peripheral device circuitry”) 914. In other examples, respective compute devices may include other or additional components, such as those typically found in a computer (e.g., a display, peripheral devices, etc.). Additionally, in some examples, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component.”)
determine an availability profile for each network path option; -Paragraph [0067] ([0067] recites, “A multi-layer Discovery and Context Monitoring Protocol (DCMP) may be utilized to maintain information about status, availability, quality, and probability of failure, degradation, or congestion, etc., of links or paths in the network(s)…”)
determine a power expenditure metric for each of the plurality of transport subsystems; -Paragraph [0087] ([0087] recites, “ AI or ML based models may be used to optimize decisions to enable multi-network connectivity with proper resiliency enhancement based on policies, (e.g., that power saving and/or bandwidth savings are maximized and optimized to handle transient fluctuations in quality without reacting strongly, dual radio operations due to reliability constraints, etc.)..” As explained above, optimization can be done based on design criterion for resilience and which may be power saving and for that power expenditure metric might be used.)
generate a sustainable network path score based on the availability profile and the power expenditure metric; select a network path based on the generated sustainable network path score; -Paragraph [0088] ([0088] recites, “The AI or ML models may compute a risk score (e.g., an inferred risk score) for a data flow over a specific network or networks and the proper multi-network connectivity transmission mode may be selected based on the risk score and/or other network conditions, such as current network performance, network latency, etc. “ It is easily understandable that the risk score might be based on power expenditure metric when the objective is power saving)
and power off the selected network path. -Paragraph [0019] ([0019] recites, “End-to-end network resiliency obtained by using AI or ML to drive a decision to turn multi-network connectivity on or off along the network path;”)
Maciocco does not explicitly teach,
based on a power source type associated with the transport subsystem;
However, in an analogous invention, Herb teaches,
based on a power source type associated with the transport subsystem; -Paragraph [0066] ([0066] recites, “Some embodiments may use telemetry values in combination with a set of obtained environmental impact scores to determine an environmental impact score associated with network paths listed in a routing table. For example, some embodiments may determine that a first network path uses a router and a switch located at a first location and a second location, respectively. Some embodiments may then use a set of telemetry values to determine an electrical energy use of the devices and an approximate proportion of power used by the data transport through the network path. Some embodiments may further determine types of power sources used to power the router and the switch, respectively, and retrieve a set of carbon generation rates (e.g., 0.91 pounds per kilowatt) based on the power sources. Some embodiments may then determine a carbon footprint score or another environmental impact score based on a product of the energy used to transport data and the carbon generation rates. For example, some embodiments may determine a carbon footprint score for a network path listed in a routing table based on a product of a data-transport-rate-to-power conversion rate equal to 0.1 watts per million bits per second and a carbon generation rates equal to 0.91 pounds per kilowatt.”)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the “Adaptive Resilient Network Communication” proposed by Maciocco to include the concept of “based on a power source type associated with the transport subsystem;” of Herb . One of ordinary skill in the art would have been motivated to make this modification in order to improve workload management in distributed computing architecture [0002].
Regarding Claim 2, Maciocco and Herb teach the limitations of Claim 1.
Maciocco further teaches,
The device of claim 1, wherein the network path options are identified within a set of devices. -Paragraph [0038][0027][0090] ([0038] recites, “When the tolerance settings are exceeded, a policy engine may trigger one or more steps to “turn on” or implement, increase the degree of, or to change options for the multi-network connectivity. For example, the policy engine may initiate an exploration process or procedure to identify possible or candidate paths or links for establishing the multi-network connectivity” [0027] recites. “ As illustrated in FIG. 1, the user equipment 100 may include individual devices such as a computer, a cellular phone, a tablet, or a vehicle connected with wireless connectivity, or may include multiple devices such as all the computers or similar devices located in a building, such as an office building, a stadium, a mall, a garage, or the like. The user equipment 100 may have connectivity with networks of different types such as a satellite network 102, a mobile or cellular network 104, a wireless network 106, or a wired network such as a broadband network 108. The network destination may include an internet connected cloud service 110, or any similar destination. The user equipment 100 may be connected to the various networks through native network connections (as illustrated by the solid interconnecting lines) via different access points. For example, the user equipment 100 may be connected to the satellite network 102 through radio access, be connected to the cellular network 104 via communication with a cell tower 112, to the wireless network 106 via a router 114, and to the broadband network 108 via a wired connection such as an optical line 116. “ [0090] recites, “For example, the traffic 302 may be received from the one or more control units 120 in the cellular network 104, the one or more routers 128 connecting the cellular access network to the core network 126, the one or more additional control units 132 of the core network 126, or the like. To conserve space in the figure, only the satellite network 102 and the cellular network 104 and some of the components illustrated in FIG. 1 are reproduced, but it is understood that the traffic 302 that the decision making model 300 receives may be from any of the networks described herein (or any networks similar to those), and from any of the pathways and/or components (or any similar pathways and components) of the networks.” As mentioned above, there are many different path options for the multi-network connectivity between user device and network device to communicate.)
Regarding Claim 3, Maciocco and Herb teach the limitations of Claim 2.
Maciocco further teaches,
The device of claim 2, wherein the set of devices is within a managed network domain. -Fig. 5 (502, 504); Paragraph [0024] ([0024] recites. “the system may monitor several different networks, which may include different types of networks. The network types may include a satellite network, a broadband network, a wireless network (e.g., a wireless Local Area Network (LAN), a wireless Metropolitan Area Network (MAN), a wireless Personal Area Network (PAN), a wireless Wide Area Network (WAN), or the like), or a cellular or mobile network (e.g., a 4G network, a 5G network, or the like) as discussed below, and that the pathways discussed may include a path, a component (e.g., a router, a socket, a node, etc.), a link, a function, a specification, or the like for one or more of the several different networks.” The devices within the pathways to the managed networks are monitored as Shown in Fig. 5 (502, 504).
Regarding Claim 4, Maciocco and Herb teach the limitations of Claim 1.
Maciocco further teaches,
The device of claim 1, wherein the device is in communication with a plurality of client applications. -Paragraph [0016][0135] ([0016] recites, “For example, some approaches have proposed use of active-active redundancy (in which an active primary and an active backup system serve clients simultaneously and interchangeably so if one system fails, clients or services are migrated to the remaining active system) or active-passive redundancy (in which the primary system is active and the backup system is passive, and only the active system serves clients, applications, or the like…” [0135] recites, “Edge computing within the Edge cloud 610 may provide the ability to serve and respond to multiple applications of the use cases 705 (e.g., object tracking, video surveillance, connected cars, etc.) in real-time or near real-time, and meet ultra-low latency requirements for these multiple applications. These advantages enable a whole new class of applications (e.g., Virtual Network Functions (VNFs), Function as a Service (FaaS), Edge as a Service (EaaS), standard processes, etc.), which cannot leverage conventional cloud computing due to latency or other limitations.” As explained above the device communicates with plurality of client applications.)
Regarding Claim 5, Maciocco and Herb teach the limitations of Claim 4.
Maciocco further teaches,
The device of claim 4, wherein the plurality of client applications has an associated service level agreement (SLA). -Paragraph [0078][0134] ([0078] recites, “..The Network Anomaly and App-Aware Operations Handler 224D on the radio access layer 210 may perform operations such as policy enforcement (e.g., enforcing a QoS or SLA policy from the application or another service, or from a policy store 226 located on the middleware layer 204)..” [0134] recites, “When a component in the transaction is missing its agreed to Service Level Agreement (SLA), the system as a whole (components in the transaction) may provide the ability to (1) understand the impact of the SLA violation, and (2) augment other components in the system to resume overall transaction SLA, and (3) implement steps to remediate.” The system tries to maintain the SLA associated with applications.)
Regarding Claim 10, Maciocco and Herb teach the limitations of Claim 1.
Maciocco further teaches,
The device of claim 1, wherein the network comprises a plurality of point-to-point paths. -Paragraph [0027] ([0027] recites, “FIG. 1 illustrates an example of interconnected heterogeneous networks. A system for adaptive resilient network protocols may monitor network traffic on multiple pathways between user equipment 100 and an application or service at a network destination. As illustrated in FIG. 1, the user equipment 100 may include individual devices such as a computer, a cellular phone, a tablet, or a vehicle connected with wireless connectivity, or may include multiple devices such as all the computers or similar devices located in a building, such as an office building, a stadium, a mall, a garage, or the like. The user equipment 100 may have connectivity with networks of different types such as a satellite network 102, a mobile or cellular network 104, a wireless network 106, or a wired network such as a broadband network 108. The network destination may include an internet connected cloud service 110, or any similar destination. The user equipment 100 may be connected to the various networks through native network connections (as illustrated by the solid interconnecting lines) via different access points. For example, the user equipment 100 may be connected to the satellite network 102 through radio access, be connected to the cellular network 104 via communication with a cell tower 112, to the wireless network 106 via a router 114, and to the broadband network 108 via a wired connection such as an optical line 116.”)
Regarding Claim 11, Maciocco and Herb teach the limitations of Claim 10.
Maciocco further teaches,
The device of claim 10 wherein the sustainable network path scores are generated for each of the plurality of point-to-point paths. -Paragraph [0088] ([0088] recites, “The AI or ML models may compute a risk score (e.g., an inferred risk score) for a data flow over a specific network or networks and the proper multi-network connectivity transmission mode may be selected based on the risk score and/or other network conditions..” As explained above, risk score is computed over different paths (path score) over different network in point-to-point manner)
Regarding Claim 12, Maciocco and Herb teach the limitations of Claim 11.
Maciocco further teaches,
The device of claim 11, wherein the generated sustainable network path scores for each point-to-point path are stored upon generation. -Paragraph [0088] ([0088] recites, “The AI or ML models may compute a risk score (e.g., an inferred risk score) for a data flow over a specific network or networks and the proper multi-network connectivity transmission mode may be selected based on the risk score and/or other network conditions..” As explained above, proper multi-network connectivity mode is selected based on the computed score and therefore, it is imperative that the scores are stored and compared for the selection process.)
Regarding Claim 13, Maciocco and Herb teach the limitations of Claim 1.
Maciocco further teaches,
The device of claim 1, wherein the network path optimization logic can be configured to generate a new sustainable network path score in response to a predefined event. -Paragraph [0087-0089] ([0087] recites, “AI or ML based models may be used to optimize decisions to enable multi-network connectivity with proper resiliency enhancement based on policies, (e.g., that power saving and/or bandwidth savings are maximized and optimized to handle transient fluctuations in quality without reacting strongly, dual radio operations due to reliability constraints, etc.). AI or ML models may be trained on policy data and may be used to infer or estimate traffic prediction, network status prediction, or the like, thus providing guidelines for conditions to enable multi-network connectivity and determine which resilient mode to use (e.g., which mitigation step(s) to implement or employ)” [0089] recites, “..When the inferred risk score falls between the thresholding values, then an inference is drawn more frequently (the risk score is computed more frequently) until a moving window average for the risk score, along with the latest value of the risk score itself, has either dropped below to or crossed above ti. After a multi-network connectivity mitigation step is chosen for a session for which the previous default was not to implement multi-network connectivity, the risk score may be similarly re-evaluated with the thresholds..” As explained, the optimization logic may generate new risk score (network path score) in response to connectivity mitigation step if required.)
Regarding Claim 14, Maciocco and Herb teach the limitations of Claim 13.
Maciocco further teaches,
The device of claim 13, wherein the predefined event is detecting a change in the identified network path options. -Paragraph [0038][0085] ([0038] recites, “..When the tolerance settings are exceeded, a policy engine may trigger one or more steps to “turn on” or implement, increase the degree of, or to change options for the multi-network connectivity. For example, the policy engine may initiate an exploration process or procedure to identify possible or candidate paths or links for establishing the multi-network connectivity…”)
Regarding Claim 15, Maciocco and Herb teach the limitations of Claim 13.
Maciocco further teaches,
The device of claim 13, wherein the predefined event is a network failure detection. -Paragraph [0016]( [0016] recites, “Some attempts at network resiliency have been tried using both hardware-based and software-based solutions. For example, some approaches have proposed use of active-active redundancy (in which an active primary and an active backup system serve clients simultaneously and interchangeably so if one system fails, clients or services are migrated to the remaining active system) or active-passive redundancy (in which the primary system is active and the backup system is passive, and only the active system serves clients, applications, or the like, and if the active system fails, the backup system activates and clients and services are migrated to the backup system) to detect network failure and switch clients or services to other devices or systems…”)
Regarding Claim 16, Maciocco and Herb teach the limitations of Claim 13.
Maciocco further teaches,
The device of claim 13, wherein the predefined event is a service level agreement (SLA) change detection. -Paragraph [0098] ([0098] recites, “..The network monitoring system may also factor how networking “knobs” on the protocol layer may affect the performance and dynamically tune the knobs. The knobs may be tuned, for example, in response to SLA or QoS requirements dictated by the service. The network may provide feedback to a software stack, which may be used to change communication schemes based on the current infrastructure state. ..” As explained above, when SLA change is detected because of different service has different SLA or QoS requirement, the network monitoring system might adjust by tuning the knob dynamically)
Claim 17 is the method claim corresponding to the apparatus Claim 1 which is rejected above. Applicant’s attention is drawn towards the rejection of Claim 1. Claim 17 is rejected under the same rational as Claim 1.
Regarding Claim 18, Maciocco and Herb teach the limitations of Claim 17.
Maciocco further teaches,
The method of claim 17, wherein powering off of a selected network path does not violate a service level agreement (SLA). -Paragraph [0019] [0078]([0019] recites, “End-to-end network resiliency obtained by using AI or ML to drive a decision to turn multi-network connectivity on or off along the network path;” [0078] recites, “The Network Anomaly and App-Aware Operations Handler 224C on the network layer 208 may perform operations such as content, traffic, or data forwarding or prioritization. The Network Anomaly and App-Aware Operations Handler 224D on the radio access layer 210 may perform operations such as policy enforcement (e.g., enforcing a QoS or SLA policy from the application or another service, or from a policy store 226 located on the middleware layer 204), or implementing multi-network connectivity such as at the user equipment 100 level (e.g., switching the user equipment 100 from one type of network to another or activating a second network connection and sending data or traffic across both networks).” From the above description, it is clear that even if selected network path is powered off, the SLA policy is enforced and is not violated)
Regarding Claim 19, Maciocco and Herb teach the limitations of Claim 18.
Maciocco further teaches,
The method of claim 17, wherein the method further powers on a selected network path based on the generated sustainable network path score to avoid a violation of a service level agreement (SLA). -Paragraph [0089] ([0089] recites, “..When the inferred risk score falls between the thresholding values, then an inference is drawn more frequently (the risk score is computed more frequently) until a moving window average for the risk score, along with the latest value of the risk score itself, has either dropped below to or crossed above ti. After a multi-network connectivity mitigation step is chosen for a session for which the previous default was not to implement multi-network connectivity, the risk score may be similarly re-evaluated with the thresholds..” [0078] recites, “The Network Anomaly and App-Aware Operations Handler 224C on the network layer 208 may perform operations such as content, traffic, or data forwarding or prioritization. The Network Anomaly and App-Aware Operations Handler 224D on the radio access layer 210 may perform operations such as policy enforcement (e.g., enforcing a QoS or SLA policy from the application or another service, or from a policy store 226 located on the middleware layer 204), or implementing multi-network connectivity such as at the user equipment 100 level (e.g., switching the user equipment 100 from one type of network to another or activating a second network connection and sending data or traffic across both networks).” Based on Network path scores, second network path might be activated (power on) and send traffic/data on the newly selected network path or on both network paths to guarantee SLA)
Regarding Claim 20, It is a combination of Claims 1, 3, 4 which are rejected above. Applicant’s attention is directed towards Claim 1, 3, 4. Maciocco further teaches (the additional parts)
adjust the energy usage of the selected network path; detect a change in an associated SLA; determine a new availability profile based on the changed SLA; generate an updated sustainable network path score based on the new availability profile; select an updated network path based on the updated sustainable network path score; and re-adjust the energy usage of the selected network path. -Paragraph [0098] ([0098] recites, “..The network monitoring system may also factor how networking “knobs” on the protocol layer may affect the performance and dynamically tune the knobs. The knobs may be tuned, for example, in response to SLA or QoS requirements dictated by the service. The network may provide feedback to a software stack, which may be used to change communication schemes based on the current infrastructure state. ..” [0089] recites, “..When the inferred risk score falls between the thresholding values, then an inference is drawn more frequently (the risk score is computed more frequently) until a moving window average for the risk score, along with the latest value of the risk score itself, has either dropped below to or crossed above ti. After a multi-network connectivity mitigation step is chosen for a session for which the previous default was not to implement multi-network connectivity, the risk score may be similarly re-evaluated with the thresholds..”)
Claims 6, 7 are rejected under 35 U.S.C. 103 as being unpatentable over Maciocco
in view of Herb and further in view of Yeh et al. (Patent No: US20220124560A1), hereinafter, Yeh.
Regarding Claim 6, Mariocco and Herb teach the limitations of Claim 5.
Mariocco does not explicitly mention
The device of claim 5, wherein the availability profile is determined based on the client application SLAs.
However, Yeh teaches
The device of claim 5, wherein the availability profile is determined based on the client application SLAs. -Paragraph [0488] ([0488] recites, “The term “service level objective” or “SLO” at least in some embodiments refers to one or more measurable characteristics, metrics, or other aspects of an SLA such as, for example, availability, throughput, frequency, response time, latency, QoS, QoE, and/or other like performance metrics/measurements…” As stated above availability profile is based on client application SLAs)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the “Adaptive Resilient Network Communication” proposed by Maciocco to include the concept of “availability profile is determined based on the client application SLAs.” of Yeh . One of ordinary skill in the art would have been motivated to make this modification in order to potentially offer unprecedented QoS improvements and enhancements [0128]
Regarding Claim 7, Mariocco, Herb and Yeh teach the limitations of Claim 6.
Mariocco does not explicitly mention,
The device of claim 6, wherein the availability profile is determined based on the SLA with the highest level of availability.
However, Yeh teaches,
The device of claim 6, wherein the availability profile is determined based on the SLA with the highest level of availability. -Paragraph [0488][0027] ([0488] recites, “The term “service level objective” or “SLO” at least in some embodiments refers to one or more measurable characteristics, metrics, or other aspects of an SLA such as, for example, availability, throughput, frequency, response time, latency, QoS, QoE, and/or other like performance metrics/measurements…”[0027] recites, “Desired properties for (ultra-)resilient network slices include reliable data transmission (e.g., including transmission with very low packet drop rate and/or guarantee of timely packet delivery); high service availability (e.g., subscribed users can always connect to the network slice service in the slice coverage area);…“ It is easily understandable from the above description that availability profile may be determined based on highest level of availability)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the “Adaptive Resilient Network Communication” proposed by Maciocco to include the concept of “availability profile is determined based on the SLA with the highest level of availability”of Yeh . One of ordinary skill in the art would have been motivated to make this modification in order to potentially offer unprecedented QoS improvements and enhancements [0128]
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Maciocco in view of Herb and further in view of Doshi et al. (Patent No: US20220113790A1), hereinafter, Doshi.
Regarding Claim 8, Maciocco and Herb teaches the limitations of Claim 1.
Maciocco explicitly does not teach,
The device of claim 1, wherein the power expenditure metric is determined based on an expected bandwidth usage
However, Doshi teaches,
The device of claim 1, wherein the power expenditure metric is determined based on an expected bandwidth usage. -Fig. 15; Paragraph [0049][0182] ([0049] recites,” The Edge may be power and cooling constrained and therefore the power usage needs to be accounted for by the applications that are consuming the most power. There may be inherent power-performance tradeoffs in these pooled memory resources, as many of them are likely to use emerging memory technologies, where more power requires greater memory bandwidth…” [0182] recites, “…FIG. 15 monitor the power intent and actual power metrics during execution in addition to the long-term SLA (or SLO policies derived therefrom) and metrics of the actual execution. These deltas are used as control loop feedback to a fine-grained control to modify PL1 or PL2 settings or execution priorities. The implementation illustrated in FIG. 15 may be like Dynamic Resource Control (DRC), which is used to continually retune allocation of processor cache capacity and memory bandwidth to processes, virtual machines, containers, etc., in order to close the gap between performance objectives (e.g., SLO) and measured performance” As explained above, this is a constrained optimization and power metric is determined based on the bandwidth usage)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the “Adaptive Resilient Network Communication” proposed by Maciocco to include the concept of “the power expenditure metric is determined based on an expected bandwidth usage ”of Doshi . One of ordinary skill in the art would have been motivated to make this modification in order to having continuous improvement capabilities and enabling self-adaptation, self-healing, and optimization in the system [0142]
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Maciocco
in view of Herb, Doshi and further in view of Norris et al. (Patent No: US20240264650A1), hereinafter, Norris.
Regarding Claim 9, Maciocco, Herb and Doshi teach the limitations of Claim 8.
Maciocco explicitly does not teach,
The device of claim 8, wherein the power expenditure metric is determined based on all available bandwidth including currently powered down transport subsystems.
However, Norris teaches,
The device of claim 8, wherein the power expenditure metric is determined based on all available bandwidth including currently powered down transport subsystems. -Paragraph [0013] ([0013] recites, “For instance, network elements (e.g., each network element) may be capable of monitoring and recording different aspects of their power consumption in one or more monitored variables/parameters over time—e.g., current power utilization and/or other power metric, such as power efficiency, power quality, etc.—and providing this information to a corresponding domain management controller, the central domain controller, and/or other network elements. In certain embodiments, network elements (e.g., each network element) may be capable of additionally providing information regarding (or usable to ascertain) device capacity, such as available bandwidth, device latency, and/or the like, to a corresponding domain management controller, the central domain controller, and/or other network elements. In one or more embodiments, the central domain controller may based upon obtaining power-related and capacity-related information, determine power-related values or metric(s) for identified candidate service routes across one or more of the different domains. In certain embodiments, the central domain controller may determine possible routes through the transport network (e.g., that have sufficient capacity based on the service requirements), calculate power-related metric(s) for the various network elements in the different domains to identify end-to-end power metric impact of the service for those possible routes, and cause some or all of the identified candidate service routes and their corresponding power-related values or metric(s) to be provided to a user or routing system or algorithm for review/selection.” As explained above, power utilization (expenditure) metric is based on the available bandwidth)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the “Adaptive Resilient Network Communication” proposed by Maciocco to include the concept of “the power expenditure metric is determined based on all available bandwidth including currently powered down transport subsystems” of Norris . One of ordinary skill in the art would have been motivated to make this modification in order to design a defined set of services to being a next generation, multi-service transport platform that is flexible, intelligent, open, and power efficient [0014]
Response to Argument(s)
Applicant’s arguments with respect to the claims have been considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/AHMED SAIFUDDIN/Examiner, Art Unit 2475
/ABDULLAHI AHMED/ Examiner, Art Unit 2475